JCB J Circ Biomark 2023; 12: 1-11ISSN 1849-4544 | DOI: 10.33393/jcb.2023.2479ORIGINAL RESEARCH ARTICLE Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb © 2023 The Authors. This article is published by AboutScience and licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Commercial use is not permitted and is subject to Publisher’s permissions. Full information is available at www.aboutscience.eu is still one of the main ophthalmic public health conditions in developed and developing countries (3). Cataracts are mainly divided into nuclear cataract (NC), cortical cataract (CC), posterior sub capsular (PSC) cataract, acquired cataract and congenital cataract (4). Senile cataract is one of the common types of acquired cataract which occurs as a consequence of the aging process. It is characterized by initial opacity in the lens with subsequent swelling of lens and final shrinkage with complete loss of transparency (5). Cataract is detected by an eye examination that includes a visual activity test, slit lamp exam (SLE) and dilated eye exam (6). Worldwide, cataract has caused >50% vision loss includ- ing 33.4% blind people and 18.4% people with moderate to severe visual impairment. Globally 10.8 million people were blind and 35.1 million people were visually impaired from cataract in 2010 (7). Additionally, data from the World Health Organization (WHO) has estimated that this number will increase to 40 million in 2025 due to the aging populations with greater life expectancies (8). Up to 50 million people in Impact of clinico-biochemical variations on the etiopathogenesis of cataract: a case-control study Tabassum Rashid1, Syed Sadaf Altaf2, Shabhat Rasool1, Rabiya Iliyas1, Sabia Rashid2, Sabhiya Majid1, Mosin Saleem Khan1,3 1 Department of Biochemistry, Government Medical College and Associated SMHS and Super Speciality Hospital, Karan Nagar, Srinagar, Jammu & Kashmir - India 2 Department of Ophthalmology, Government Medical College Srinagar and Associated SMHS and Super Speciality Hospital, Karan Nagar, Srinagar, Jammu & Kashmir - India 3 Department of Biochemistry, Government Medical College Baramulla and Associated Hospitals, Kanth Bagh, Baramulla, Jammu & Kashmir - India ABSTRACT Purpose: Cataract is a major cause of blindness worldwide with a greater prevalence in developing countries like India. Owing to speculations about the relationship of various biochemical markers and cataract formation this case-control study was designed with the aim to know the impact of serum blood sugar, serum electrolytes and serum calcium on the etiopathogenesis of cataract in Kashmiri population. Methods: A total of 300 cases diagnosed with cataract and 360 healthy controls were taken for the study. Serum of all the cases and controls was analyzed for blood sugar and calcium using spectrometric techniques. Sodium and potassium were analyzed using Ion-Selective Electrode technology. All the investigations were done on ABBOTT c4000 fully automatic clinical chemistry analyzer. Results: Most of the patients in our study were ≥50 years of age having posterior subcapsular cataract. The mean levels of serum fasting blood sugar (mg/dL), serum sodium (mmol/L), serum potassium (mmol/L) and serum calcium (mg/dL) were 99.4 ± 7.7; 140.4 ± 2.5; 4.2 ± 0.5; and 8.9 ± 0.5, respectively, in cases compared to 107.7 ± 12.3; 142.9 ± 5.0; 3.8 ± 0.5; and 8.3 ± 1.7, respectively, in healthy controls. A significantly higher number of cata- ract cases had elevated serum glucose and sodium levels, low serum potassium and calcium levels compared to healthy controls. Conclusions: Hyperglycemia, hypernatremia, hypokalemia and hypocalcemia can independently increase the patients’ risk to cataracts. Corrections in these biochemical parameters may reduce cataract incidence. Keywords: Blood pressure, Blood sugar, Calcium, Cataract, Intraocular pressure, Potassium, Sodium Received: August 3, 2022 Accepted: December 21, 2022 Published online: January 16, 2023 Corresponding author: Dr. Mosin Saleem Khan Assistant Professor Department of Biochemistry Government Medical College Baramulla & Associated Hospitals Kanth Bagh - 193101, Baramulla, Jammu & Kashmir - India mosinsaleemkhan@gmail.com Introduction The International Agency for the Prevention of Blindness has defined cataract as the clouding or opacification of the normally clear lens of the eye or its capsule that obscures the passage of light through the lens to the retina (1,2). This dis- ease, which can significantly reduce patient’s quality of life, https://doi.org/10.33393/jcb.2023.2479 https://creativecommons.org/licenses/by-nc/4.0/legalcode mailto:mosinsaleemkhan@gmail.com Biochemical markers in cataract2 © 2023 The Authors. Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb the world suffer from senile cataract (9,10), and its preva- lence in developing countries is much more than in devel- oped ones (11). In India, the prevalence of blindness due to cataract was reported to be 8% in the age group of >50 years, as per the National blindness survey (12). An estimated 20 lakh new cases of cataract are being added to the burden every year in this country, showing a steep rise ranging from 0.5% above 30 years to 94.5% above 70 years (13). Cataract accounts for 62.6% of all blindness, affecting 9-12 million bilaterally blind persons (14). The WHO/NPCB (National Programme for Control of Blindness) survey has shown that there are over 22 million blind in India and 80.1% of these are blind due to cataract (15). Cataract is caused by degeneration and opacification of the lens fibers already formed. Any factor that disturbs the critical intra- and extracellular equilibrium of water and elec- trolytes or deranges the colloid system within the fibers tends to bring about opacification (16). Several studies have been carried out to elucidate risk factors which are responsible for development of cataract. Extensive research has estab- lished age, ion imbalance, altered calcium levels, diabetes and UV light exposure as causative risk factors for cataract, while recent studies have identified other potential risk fac- tors like exogenous estrogen, nutrition, dietary fat and genet- ics which might play a role in the development of cataract (17). Although cataract affects all age groups its incidence increases with advancing age (18). Senile cataract affects equally persons of either gender, usually above the age of 50 years (19). The association between diabetes and cataract formation has been shown in clinical, epidemiological and basic research studies. Due to increasing numbers of type 1 and type 2 diabetics worldwide, the incidence of diabetic cat- aracts steadily rises (20). Several clinical studies have shown that cataract development occurs more frequently and at an earlier age in diabetic compared to nondiabetic patients (20). Many studies have shown that serum electrolyte (potassium and sodium) concentration directly affects the concentra- tion of electrolytes in aqueous humor and thereby induces cataract formation. Concentration of sodium in lens is less compared to serum concentrations whereas it is vice versa in case of potassium concentrations, and this cationic bal- ance is maintained by the osmotic pressure and thus water balance by the action of enzyme Na+/K+ ATPase. Any imbal- ance in between the electrolytes leads to cataract formation (21). Calcium is of particular concern in cataract. This cation is essential for various lens fiber cell metabolism processes (22). It has been shown that lens calcium content correlates with opacity in cataractous human lenses (23) and subse- quent changes in serum calcium concentration might be an important factor in the development of cataract (24). Demographic and clinico-biochemical biomarkers have been previously linked with the development of cataract from other parts of the world, but so far only few studies have been reported from the Indian subcontinent regarding the interrelationship of cataract (25,26). Keeping in view the ethnicity and relatively conserved genetic pool of Kashmiri population, this case-control study was designed to elucidate the role of demographic and clinico-biochemical parameters in the etiopathogenesis and severity of cataract in Kashmiri population. Materials and methods Ethics This study was performed in line with the principles of the Declaration of Helsinki. Ethical clearance for the study was sought from Institutional Review Board, Government of Medical College Srinagar vide No. 2022T/ETH/GMC. All the patients included in the study were informed about the study and informed consent both in vernacular as well as in English language was taken before eliciting history and sample collection from study subjects. Standard ques- tionnaire or patient proforma was properly recorded and drafted as per socio-demographic and clinico-biochemical parameters. The authors affirm that human research par- ticipants provided informed consent for publication of their details. Study design This was a case-control study conducted by the Department of Biochemistry in collaboration with the Department of Ophthalmology, Government Medical College Srinagar and associated SMHS hospital Srinagar, J&K, from March 2020 to March 2022. Study subjects and sample size The study was conducted in ethnic population of Kashmir; no restrictions were made among patients with respect to gender and dwelling. A total of 300 patients diagnosed with cataract and 360 healthy controls were enrolled for the study. Keeping the power of study as 80% and allocation ratio of 1.2 and effect size of 0.4, the sample size was calculated by G power 23.0.1 version. Inclusion and exclusion criteria “Cases” included all those individuals who were >18 years of age and diagnosed with cataract. “Cases” excluded all those individuals with any other eye ailment and symp- tomatic disease (liver, kidney, heart or other), trauma, infection, inflammation of eye, cancer or any other genetic abnormality. “Controls” included healthy individuals >18 years of age. Ophthalmic examination Each patient was subjected to various ophthalmic mea- surements. Uncorrected visual acuity was measured with Snellen chart. Refraction was done and the best corrected visual acuity was noted. Intraocular pressure (IOP) measure- ment was done with non-contact tonometer. Corrected IOP was calculated after measuring central corneal thickness by ultrasonic pachymetry. Detailed anterior segment examina- tion using slit lamp was done to rule glaucoma and associ- ated ocular pathology. Detailed fundus examination under full mydriasis obtained by 0.8% tropicamide and 5% phenyl- ephrine was done with direct ophthalmoscopy, 78D and indi- rect ophthalmoscopy. Rashid et al J Circ Biomark 2023; 12: 3 © 2023 The Authors. Published by AboutScience - www.aboutscience.eu Sample collection A total of 04 mL of venous blood was collected from each cataract patient and healthy control in a coagulation activat- ing red top vial. Blood was collected from each individual after 8-10 hours of fasting. Blood was immediately centri- fuged for separation of serum. Serum was properly stored at ‒20°C till biochemical analysis was done in the Biochemistry diagnostic laboratory, SMHS hospital Srinagar. Biochemical analysis for electrolytes Serum electrolyte levels were estimated on ABBOTT ARCHITECT c4000 fully automated clinical chemistry analyzer using Ion-Selective Electrode. The reference ranges of serum sodium levels were taken between 135 and 145 mmol/L and serum potassium levels as 3.5-4.5 mmol/L. Biochemical analysis for calcium Serum calcium levels were estimated spectrophotometri- cally on ABBOTT ARCHITECT c4000 fully automated clinical chemistry analyzer using Arsenazo III dye. The reference ranges of serum calcium were taken as: 8.5-10.2 mg/dL. Biochemical analysis of glucose Serum glucose levels were measured spectrophotometri- cally on ABBOTT ARCHITECT c4000 fully automated clinical chemistry analyzer. Glucose is phosphorylated by hexokinase (HK) in the presence of adenosine triphosphate (ATP) and magnesium ions to produce glucose-6-phosphate (G6P) and adenosine diphosphate (ADP). Glucose-6-phosphate dehydro- genase (G6PDH) specifically oxidizes G6P to 6-phosphogluco- nate with the concurrent reduction of nicotinamide adenine dinucleotide (NAD) and readily to nicotinamide adenine dinu- cleotide reduced (NADH). One micromole of NADH is produced for each micromole of glucose consumed. The NADH produced absorbs light at 340 nm and can be detected spectrophoto- metrically as an increased absorbance. The reference ranges of serum glucose were taken as: 99-100 mg/dL (normal) and >100 mg/dL (impaired). Statistical analysis The data was analyzed using IBM Statistical Package for the Social Sciences (SPSS) software v. 25.0. Descriptive sta- tistics was performed and data was presented as frequency (N) and percentage (%). Continuous data was presented as mean and standard deviation. Chi-square test was used to compare proportions between groups as deemed proper by the statistical expert. P value <0.05 was considered statisti- cally significant. Results Table I contains the socio-demographic and clinicopatho- logical characteristics of cataract cases and healthy controls. Cases and controls were matched with respect to age and gender; 17.5% (63 of 360) of the controls were <50 years of age as compared to 21% (63 of 300) of cases who were <50 years of age. With respect to gender, 47.5% (171 of 360) controls were men as compared to 52.0% (156 of 300) of men having cataract. Accordingly, 90.0% (324 of 360) of the controls were inhabitants of rural areas as compared to 80% (240 of 300) of cases who belonged to rural areas. The cata- ract patients were evaluated for various clinical parameters. Hypertension was present in 13.0% (39 of 300) of cataract patients. The family history of cataract was present in 4.0% (12 of 300) of cases. The history of any other eye disorder was present in 23.0% (69 of 300) of cataract cases. Further the IOP of all the patients was measured wherein 91.0% (273 of 300) had normal IOP while 9.0% (27 of 300) had higher IOP. TABLE I - Socio-demographic and clinicopathological characteris- tics of cases having cataract and controls included in the study – Controls N = 360 (%) Cases N = 300 (%) χ2 p value Age group <50 years ≥50 years 63 (17.5) 297 (82.5) 63 (21.0) 237 (79.0) 1.2 0.15 Gender Men Women 171 (47.5) 189 (52.5) 156 (52.0) 144 (48.0) 1.3 0.15 Dwelling Rural Urban 324 (90.0) 36 (10.0) 240 (80.0) 60 (20.0) 13.1 <0.0001 Hypertension No Yes – 261 (87.0) 39 (13.0) – – Family history of cataract No Yes – 288 (96.0) 12 (4.0) – – H/o any other eye disorder No Yes – 231 (77.0) 69 (23.0) – – Eyes affected One Both – 177 (59.0) 123 (41.0) – – Type of cataract Nuclear Cortical Posterior subcapsular – 00 (0.0) 75 (25.0) 225 (75.0) – – Grade I and II III and IV – 165 (55.0) 135 (45.0) – – IOP Normal High – 273 (91.0) 27 (9.0) – – H/o = history of; IOP = intraocular pressure. Biochemical markers in cataract4 © 2023 The Authors. Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb Table II depicts the biochemical parameters of cataract cases and healthy controls; 69.0% (207 of 300) of cases had impaired blood sugar level as compared to 22.5% (81 of 360) of controls having impaired blood sugar, and the asso- ciation was found to be statistically significant (p<0.0001); 36.3% (109 of 300) of cases had hypernatremia as compared to only 3.0% (11 of 360) of controls with hypernatremia (p<0.0001). Cataract cases had significantly low potassium levels compared to controls (17.5% vs. 6.1%; p<0.0001). In addition, 38.0% (114 of 300) of cases had hypocalcemia as compared to only 12.5% (45 of 360) of controls with hypo- calcemia and the difference was statistically significant (p<0.0001). TABLE II - Biochemical parameters of cataract cases and healthy controls Parameters Controls N = 360 (%) Cases N = 300 (%) OR (95% CI) p value Fasting blood sugar Normal Impaired 279 (77.5) 81 (22.5) 93 (31.0) 207 (69.0) 7.6 (5.4-10.8) <0.0001 Sodium levels Normal High 349 (97.0) 11 (3.0) 191 (63.7) 109 (36.3) 18.1 (9.5-34.4) <0.0001 Potassium levels Normal Low 338 (93.9) 22 (6.1) 249 (83.0) 51 (17.0) 3.1 (1.9-5.3) <0.0001 Calcium levels Normal Low 315 (87.5) 45 (12.5) 186 (62.0) 114 (38.0) 4.2 (2.9-6.3) <0.0001 CI = confidence interval; OR = odds ratio. Table III shows the mean levels of various biochemical parameters in cases and healthy controls. A statistically sig- nificant difference was observed between cases and controls with respect to mean fasting blood sugar levels in mg/dL (107.7 ± 12.3 vs. 99.4 ± 7.7); mean sodium levels in mmol/L (142.9 ± 5.0 vs. 140.4 ± 2.5); mean potassium level in mmol/L (3.8 ± 0.5 vs. 4.2 ± 0.5); mean calcium level in mg/dL (8.3 ± 1.7 vs. 8.9 ± 0.5). TABLE III - Levels (mean ± SD) of various biochemical parameters in cataract cases and healthy controls Parameters Controls (mean ± SD) Cases (mean ± SD) p value Fasting blood sugar (mg/dL) 99.4 ± 7.7 107.7 ± 12.3 <0.0001 Sodium levels (mmol/L) 140.4 ± 2.5 142.9 ± 5.0 <0.0001 Potassium levels (mmol/L) 4.2 ± 0.5 3.8 ± 0.5 <0.0001 Calcium levels (mg/dL) 8.9 ± 0.5 8.3 ± 1.7 <0.0001 SD = standard deviation. Table IV shows the association of fasting blood sugar lev- els with various socio-demographic, clinico-pathological and biochemical parameters of cataract patients and controls. In each subgroup of age, gender, dwelling, sodium, potas- sium and calcium levels, a statistically significant difference in serum blood levels was noted between cases and controls (p<0.0001). Among patients with PSC cataract, 72.0% (162 of 225) had impaired blood sugar level as compared to CC wherein only 60% (45 of 75) had impaired blood sugar, and the difference was statistically significant (p = 0.05). No asso- ciation was found between blood sugar levels and any other parameter of cases and controls. Table V describes the association of serum sodium lev- els with various socio-demographic, biochemical and clini- copathological parameters of cataract cases and controls. A statistically significant difference in serum sodium levels was noted between cases and controls in each subgroup of age, gender, dwelling, potassium and calcium levels (p<0.0001). Among cataract patients with grade I and II disease, 41.2% (68 of 165) had high sodium levels while among cataract patients with grade III and IV disease, only 30.4% (41 of 135) had high sodium levels and the difference was statistically significant (p = 0.05). We did not observe any other param- eter influencing the sodium levels in cataract patients. Table VI displays the association of serum potassium lev- els with various socio-demographic, clinicopathological and biochemical parameters of cataract patients and controls. Among cases, 20% (48 of 240) of rural inhabitants had low potassium levels as compared to 6.5% (21 of 324) of rural control subjects having low potassium levels (p<0.0001). With respect to calcium level, 31.6% (36 of 114) of hypo- calcemia cases had hypokalemia as compared to only 2.2% (01 of 45) of hypocalcemia controls having hypokalemia, and the difference was statistically significant (p<0.0001). Among hypertensive cases, 15.4% (18 of 39) had hypokale- mia but among normotensive cases only 12.6% (21 of 261) had hypokalemia, and the difference was statistically signifi- cant (p<0.0001). Importantly, 33.3% (09 of 27) cases having high IOP were hypokalemic but among cases having normal IOP, only 15.4% (42 of 273) had hypokalemia, and the differ- ence was statistically significant (p<0.0001). No association was found between serum potassium levels and any other parameter of cases and controls. Table VII depicts the association of serum calcium lev- els with various socio-demographic, clinicopathological and biochemical parameters of cataract cases and controls. A statistically significant difference in calcium levels was noted between cases and controls in each subgroup of age, gen- der and dwelling (p<0.0001). We did not observe any other parameter influencing the calcium levels in cataract patients. Discussion We evaluated cataract patients with respect to various socio-demographic, clinicopathological and biochemical characteristics. As aging itself is a major risk factor for the development of cataract in both women and men (27), most of the cataract patients were from the age group of ≥50 years. It has been suggested that with aging the alteration Rashid et al J Circ Biomark 2023; 12: 5 © 2023 The Authors. Published by AboutScience - www.aboutscience.eu TABLE IV - Association of fasting serum glucose levels with various socio-demographic, biochemical and clinicopathological parameters of cataract cases and controls Socio-demographic/ clinicopathological/ biochemical parameters Fasting serum glucose levels in controls Fasting serum glucose levels in cases OR (95% CI) p value N = 360 (%) Normal 279 (77.5) Impaired 81 (22.5) N = 300 (%) Normal 93 (31.0) Impaired 207 (69.0) 7.6 (5.4-10.8) <0.0001 Age group <50 years ≥50 years 63 (17.5) 297 (82.5) 57 (90.5) 222 (74.7) 06 (9.5) 75 (25.3) 63 (21.0) 237 (79.0) 17 (27.0) 76 (32.1) 46 (73.0) 161 (67.9) 25.7 (9.3-70.4) 6.2 (4.2-9.1) <0.0001 <0.0001 Gender Men Women 171 (47.5) 189 (52.5) 141 (82.5) 138 (73.0) 30 (17.5) 51 (27.0) 156 (52.0) 144 (48.0) 48 (30.8) 45 (31.3) 108 (69.2) 99 (68.8) 10.5 (6.2-17.7) 5.9 (3.6-9.5) <0.0001 <0.0001 Dwelling Rural Urban 324 (90.0) 36 (10.0) 255 (78.7) 24 (66.7) 69 (21.3) 12 (33.3) 240 (80.0) 60 (20.0) 75 (31.3) 18 (30.0) 165 (68.8) 45 (70.0) 8.1 (5.5-11.9) 4.6 (1.9-11.3) <0.0001 <0.001 Sodium levels Normal Elevated 349 (97.0) 11 (3.0) 270 (77.4) 09 (81.8) 79 (22.6) 02 (18.2) 191 (63.7) 109 (36.3) 58 (30.4) 35 932.1) 133 (69.6) 74 (67.9) 7.8 (5.2-11.6) 9.5 (1.9-46.3) <0.0001 0.002 Potassium levels Normal Low 338 (93.9) 22 (6.1) 261 (77.2) 18 (81.8) 77 (22.8) 04 (18.2) 249 (83.0) 51 (17.0) 84 (33.7) 09 (17.6) 165 (66.3) 42 (82.4) 6.6 (4.6-9.5) 21 (5.7-77.1) <0.0001 <0.0001 Calcium levels Normal Low 315 (87.5) 45 (12.5) 246 (78.1) 33 (73.3) 69 (21.9) 12 (26.7) 186 (62.0) 114 (38.0) 60 (32.3) 33 (28.9) 126 (67.7) 81 (71.1) 7.4 (4.9-11.2) 6.7 (3.1-14.6) <0.0001 <0.0001 Hypertension No Yes – – – 261 (87.0) 39 (13.0) 78 (29.9) 15 (38.5) 183 (70.1) 24 (61.5) 0.6 (0.3-1.3) 0.3 Family history of cataract No Yes – – – 288 (96.0) 12 (4.0) 84 (29.2) 009 (75.0) 204 (70.8) 03 (25.0) 0.13 (0.03-0.5) 0.002 H/o any other eye disorder No Yes – – – 231 (77.0) 69 (23.0) 72 (31.2) 21 (30.4) 159 (68.8) 48 (69.6) 1.03 (0.5-1.8) 1.000 Eyes affected One Both – – – 177 (59.0) 123 (41.0) 57 (32.2) 36 (29.3) 120 (67.8) 87 (70.7) 1.1 (0.6-1.8) 0.6 Type of cataract Cortical Posterior subcapsular – – – 75 (25.0) 225 (75.0) 30 (40.0) 63 (28.0) 45 (60.0) 162 (72.0) 1.7 (0.9-2.9) 0.05 Grade I and II III and IV – – – 165 (55.0) 135 (45.0) 45 (27.3) 48 (35.6) 120 (72.7) 87 (64.4) 0.6 (0.4-1.1) 0.1 IOP Normal High – – – 273 (91.0) 27 (9.0) 81 (29.7) 12 (44.4) 192 (70.3) 15 (55.6) 0.5 (0.2-1.1) 0.12 CI = confidence interval; H/o = history of; IOP = intraocular pressure; OR = odds ratio. Biochemical markers in cataract6 © 2023 The Authors. Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb TABLE V - Association of serum sodium levels with various socio-demographic, biochemical and clinicopathological parameters of cataract cases and controls Socio-demographic/ clinicopathological/ biochemical parameters Serum sodium levels in controls Serum sodium levels in cases OR (95% CI) p value N = 360 (%) Normal 349 (97.0) High 11 (3.0) N = 300 (%) Normal 191 (63.7) High 109 (36.3) 18.1 (9.5 -34.4) <0.0001 Age group <50 years ≥50 years 63 (17.5) 297 (82.5) 63 (100.0) 286 (96.3) 0 (0.0) 11 (3.7) 63 (21.0) 237 (79.0) 25 (39.7) 166 (70.0) 38 (60.3) 71 (30.0) – 11.1 (5.7-21.5) <0.0001 <0.0001 Gender Men Women 171 (47.5) 189 (52.5) 162 (94.7) 187 (98.9) 09 (5.3) 02 (1.1) 156 (52.0) 144 (48.0) 99 (63.5) 92 (63.9) 57 (36.5) 52 (36.1) 10.3 (4.9-21.8) 52.8 (12.5-221.7) <0.0001 <0.0001 Dwelling Rural Urban 324 (90.0) 36 (10.0) 314 (96.9) 35 (97.2) 10 (3.1) 01 (2.8) 240 (80.0) 60 (20.0) 150 (62.5) 41 (68.3) 90 (37.5) 19 (31.7) 18.8 (9.5-37.2) 16.2 (2.0-127.3) <0.0001 <0.0001 Potassium levels Normal Low 338 (93.9) 22 (6.1) 329 (97.3) 20 (90.9) 09 (2.7) 02 (9.1) 249 (83.0) 51 (17.0) 162 (65.1) 29 (56.9) 87 (34.9) 22 (43.1) 19.6 (9.6-39.9) 7.1 (3.8-13.3) <0.0001 <0.0001 Calcium levels Normal Low 315 (87.5) 45 (12.5) 304 (96.5) 45 (100.0) 11 (3.5) 00 (0.0) 186 (62.0) 114 (38.0) 121 (61.5) 70 (61.4) 65 (34.9) 44 (38.6) 14.8 (7.5-29.0) – <0.0001 <0.0001 Hypertension No Yes – – – 261 (87.0) 39 (13.0) 165 (63.2) 26 (66.7) 96 (36.8) 13 (33.3) 0.9 (0.4-1.7) 0.7 Family history of cataract No Yes – – – 288 (96.0) 12 (4.0) 184 (63.9) 07 (58.3) 104 (36.1) 05 (41.7) 1.2 (0.3-4.0) 0.7 H/o any other eye disorder No Yes – – – 231 (77.0) 69 (23.0) 153 (66.2) 38 (55.1) 78 (33.8) 31 (44.9) 1.6 (0.9-2.7) 0.11 Eyes affected One Both – – – 177 (59.0) 123 (41.0) 119 (67.2) 72 (58.5) 58 (32.8) 51 (41.5) 1.4 (0.9-2.3) 0.14 Type of cataract Cortical Posterior subcapsular – – – 75 (25.0) 225 (75.0) 53 (70.6) 138 (61.3) 22 (29.3) 87 (38.6) 1.5 (0.8-2.6) 0.16 Grade I and II III and IV – – – 165 (55.0) 135 (45.0) 97 (58.8) 94 (69.6) 68 (41.2) 41 (30.4) 0.6 (0.3-1.0) 0.052 IOP Normal High – – – 273 (91.0) 27 (9.0) 175 (64.1) 16 (59.3) 98 (35.9) 11 (40.7) 1.2 (0.5-2.7) 0.6 CI = confidence interval; H/o = history of; IOP = intraocular pressure; OR = odds ratio. Rashid et al J Circ Biomark 2023; 12: 7 © 2023 The Authors. Published by AboutScience - www.aboutscience.eu TABLE VI - Association of serum potassium levels with various socio-demographic, biochemical and clinicopathological parameters of cata- ract cases and controls Socio-demographic/ clinicopathological/ biochemical parameters Serum potassium levels in controls Serum potassium levels in cases OR (95% CI) p value N = 360 (%) Normal 338 (93.9) Low 22 (6.1) N = 300 (%) Normal 249 (83.0) Low 51 (17.0) 3.1 (1.9-5.3) <0.0001 Age group <50 years ≥50 years 63 (17.5) 297 (82.5) 62 (98.4) 276 (92.9) 01 (1.6) 21 (7.1) 63 (21.0) 237 (79.0) 48 (76.2) 201 (84.8) 15 (23.8) 36 (15.2) 19.3 (2.4-151.8) 2.3 (1.3-4.1) <0.0001 <0.0003 Gender Men Women 171 (47.5) 189 (52.5) 163 (95.3) 175 (92.6) 08 (4.7) 14 (7.4) 156 (52.0) 144 (48.0) 132 (84.6) 117 (7.4) 24 (15.4) 27 (18.8) 3.7 (1.6-8.5) 2.8 (1.4-5.7) <0.0001 <0.0002 Dwelling Rural Urban 324 (90.0) 36 (10.0) 303 (93.5) 35 (97.2) 21 (6.5) 01 (2.8) 240 (80.0) 60 (20.0) 192 (80.0) 57 (95.0) 48 (20.0) 03 (5.0) 3.6 (2.0-6.2) 1.8 (0.1-18.4) <0.0001 1.000 Calcium levels Normal Low 315 (87.5) 45 (12.5) 294 (93.3) 44 (97.8) 21 (6.7) 01 (2.2) 186 (62.0) 114 (38.0) 171 (91.9) 78 (68.4) 15 (8.1) 36 (31.6) 1.2 (0.6-2.4) 20.3 (2.6-153.2) 0.6 <0.0001 Hypertension No Yes – – – 261 (87.0) 39 (13.0) 228 (87.4) 33 (84.6) 21 (12.6) 18 (15.4) 5.9 (2.8-12.2) <0.0001 Family history of cataract No Yes – – – 288 (96.0) 12 (4.0) 240 (83.3) 09 (75.0) 48 (16.7) 03 (25.0) 1.6 (0.4-6.3) 0.4 H/o any other eye disorder No Yes – – – 231 (77.0) 69 (23.0) 195 (84.4) 54 (78.3) 36 (15.6) 15 (21.7) 1.5 (0.7-2.9) 0.27 Eyes affected One Both – – – 177 (59.0) 123 (41.0) 150 (84.7) 99 (80.5) 27 (15.3) 24 (19.5) 1.3 (0.7-2.4) 0.35 Type of cataract Nuclear Cortical Posterior subcapsular – – – 75 (25.0) 225 (75.0) 57 (76.0) 192 (85.3) 18 (24.0) 33 (14.7) 0.5 (0.2-1.0) 0.07 Grade I and II III and IV – – – 165 (55.0) 135 (45.0) 132 (80.0) 117 (86.7) 33 (20.0) 18 (13.3) 0.6 (0.3-1.1) 0.16 IOP Normal High – – – 273 (91.0) 27 (9.0) 231 (84.6) 18 (66.7) 42 (15.4) 09 (33.3) 2.7 (1.1-6.5) 0.051 CI = confidence interval; H/o = history of; IOP = intraocular pressure; OR = odds ratio. Biochemical markers in cataract8 © 2023 The Authors. Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb TABLE VII - Association of serum calcium levels with various socio-demographic, clinicopathological and biochemical parameters of cata- ract patients and controls Socio-demographic/ clinicopathological/ biochemical parameters Serum calcium levels in controls Serum calcium levels in cases OR (95% CI) p value N = 360 (%) Normal 315 (87.5) Low 45 (12.5) N = 300 (%) Normal 186 (62.0) Low 114 (38.0) 4.2 (2.9-6.3) <0.0001 Age group <50 years ≥50 years 63 (17.5) 297 (82.5) 54 (85.7) 261 (81.7) 09 (14.3) 36 (12.1) 63 (21.0) 237 (79.0) 40 (63.5) 146 (61.6) 23 (36.5) 91 (38.4) 3.4 (1.4-8.2) 4.5 (2.9-6.9) 0.007 <0.0001 Gender Men Women 171 (47.5) 189 (52.5) 147 (86.0) 168 (88.9) 24 (14.0) 21 (11.1) 156 (52.0) 144 (48.0) 96 (61.5) 90 (62.5) 60 (38.5) 54 (37.5) 3.8 (2.2-6.5) 4.8 (2.7-8.4) <0.0001 <0.0001 Dwelling Rural Urban 324 (90.0) 36 (10.0) 282 (87.0) 33 (91.7) 42 (13.0) 03 (8.3) 240 (80.0) 60 (20.0) 144 (60.0) 42 (70.0) 96 (40.0) 18 (30.0) 4.4 (2.9-6.7) 4.7 (1.2-17.3) <0.0001 0.02 Hypertension No Yes – – – 261 (87.0) 39 (13.0) 168 (64.4) 18 (46.2) 93 (35.6) 21 (53.8) 2.1 (1.0-4.1) 0.3 Family history of cataract No Yes – – – 288 (96.0) 12 (4.0) 180 (62.5) 06 (50.0) 108 (37.5) 06 (50.0) 1.6 (0.5-5.2) 0.3 H/o any other eye disorder No Yes – – – 231 (77.0) 69 (23.0) 147 (63.6) 39 (56.5) 84 (36.4) 30 (43.5) 1.3 (0.7-2.3) 0.3 Eyes affected One Both – – – 177 (59.0) 123 (41.0) 114 (64.4) 72 (58.5) 63 (35.6) 51 (41.5) 1.2 (0.7-2.0) 0.3 Type of cataract Nuclear Cortical Posterior subcapsular – – – 75 (25.0) 225 (75.0) 51 (68.0) 135 (60.0) 24 (32.0) 90 (40.0) 1.4 (0.8-2.4) 0.2 Grade I and II III and IV – – – 165 (55.0) 135 (45.0) 99 (60.0) 87 (64.4) 66 (40.0) 48 (35.6) 0.8 (0.5-1.3) 0.4 IOP Normal High – – – 273 (91.0) 27 (9.0) 171 (62.6) 15 (55.6) 102 (37.4) 12 (44.4) 1.3 (0.6-2.9) 0.5 CI = confidence interval; H/o = history of; IOP = intraocular pressure; OR = odds ratio. in membrane permeability of the lens epithelium coupled with the changes in sodium and potassium ion levels in aque- ous humor may accentuate ionic imbalance within the lens and lead to the development of cataract (28). In our study, a slightly higher percentage of men population was affected compared to women. According to different studies, women are more prone to getting most types of cataract than men. This is most likely due to lower estrogen levels after meno- pause in women (29). In our study, proportion of rural par- ticipants diagnosed with cataract was much higher compared to urban participants, which may be due to the differential exposure to contextual factors (30). Furthermore, we spec- ulate that rural areas lack quality healthcare and hygiene, hence putting inhabitants at more risk of developing cata- ract and its related complications. Our results are in line with the observations from other parts of the country report- ing significantly higher incidence of cataract in rural areas (31). We observed only 13.0% of the cataract cases to be hypertensive, but according to Lee et al hypertension could induce conformational changes to proteins in lens capsules, Rashid et al J Circ Biomark 2023; 12: 9 © 2023 The Authors. Published by AboutScience - www.aboutscience.eu thereby exacerbating the cataract formation (32). Per previ- ous reports, the risk of cataract increases with long-standing hypertension (33). Furthermore, some studies suggest that antihypertensive medications (such as diuretics and beta- blockers) are related to cataract (34). In our study, only few cataract patients had a family history of cataract. Our findings are consistent with epidemiological studies demonstrating more prevalent occurrence of age-related cataracts in close relatives of cataract patients than in the general population (35). In addition, genetic studies have shown the effect of specific genes in the development of cataractous lenses (35). Only one eye was affected in most of the cataract patients, which supports the previous findings that cataract may be present in one or both eyes but cannot spread from one eye to another (36). Most of the enrolled patients were having PSC cataract, which is the most common morphological form of cataract (37) and commonly studied across the country (38). PSC cataract produces more and faster vision deteriora- tion than other forms of cataract, and patients report earlier for cataract surgery, which may be a potential explanation for its elevated prevalence (39). Various studies are going on all over the world to clarify the relationship between biochemical elements and cata- ract formation (40), and most of the studies from differ- ent populations have not found a remarkable difference in blood biochemical elements between cataract patients and healthy controls (41-43). To further explore the biochemi- cal intricacies of cataract we evaluated the cases as well as controls for various biochemical markers and deduced the relationship, if any, between the disease development and biochemical markers. As evident from the dataset, most of the cataract patients in our study were having significantly impaired fasting blood sugar levels compared to controls. A previous study has found a significant relationship between hyperglycemia and incidence of cataracts (44). In vivo or in vitro studies showed evidence that diabetes mellitus is the cause of cataract (45,46). Cataracts have multiple etiolo- gies, one of which is chronic hyperglycemia which has been related to many systemic and ocular complications such as loss of vision. It has been suggested that the polyol via which the enzyme aldose reductase catalyzes the reduction of glucose into sorbitol is a central part of the mechanism of cataract development. The increased intracellular accumu- lation of sorbitol leads to a hyperosmotic effect, resulting in hydropic lens fibers that degenerate and form cataract (47,48). In our study population, the frequency of cataract patients having hypernatremia was significantly higher com- pared to controls, which is in line with the study conducted by Mathur and Pai who reported significant hypernatremia in cataract patients compared to the controls (49). Since the lens metabolism is associated with aqueous humor, which itself is produced from blood secretions, serum electrolyte concentration directly affects electrolytes of aqueous humor and in turn lens metabolism (26). Studies have upheld that, in case of increased concentrations of sodium in aque- ous humor, it is difficult for the sodium pumps to main- tain a low intracellular sodium ion level. In turn, a higher sodium ion concentration of the aqueous humor, coupled with an altered membrane permeability of lens, increases the intracellular sodium ion concentration leading to hydra- tion of the lens, thereby resulting in loss of its transparency and development of cataract (50). In the current study, we observed hypokalemia in significantly higher number of cataract patients compared to controls. Several studies revealed strong association of low serum potassium levels with CCs (51,52). According to Duncan and Bushell, cortical and mature cataracts had very low serum potassium levels (53). The frequency of hypocalcemia in cataract cases was significantly higher compared to controls. Low serum cal- cium levels in cataract patients were seen in other popula- tions, clearly supporting our results (54). Cataract is the most common ocular symptom of hypocalcemia (55). Seemingly, because of deposition of calcium in soft tissues producing reduced vision/cataract or calcification of basal ganglia, cal- cium gets depleted in human serum (56). In the further part of the study we deciphered the effect of various factors on the relationship between biochemi- cal parameters and cataract. Surprisingly none of the fac- tors significantly affected the relationship of serum glucose, serum sodium and serum calcium with cataract. In addition, we have also identified various factors modifying the asso- ciation between hypokalemia and cataract. The frequency of hypokalemic rural cataract patients was significantly higher compared to rural hypokalemic controls. Difference in mean serum potassium concentrations among Kashmiri cataract cases and healthy controls residing in rural locations might be due to difference in the quality of diet among the two groups (56,57). Interestingly we observed a significantly higher pro- portion of hypokalemic cataract patients coexistent with hypocalcemia. Although hypokalemia and hypocalcemia exhibit multiple interrelated acid-base and electrolyte abnor- malities such as hypophosphatemia, respiratory/metabolic alkalosis, mixed acid-base disorders (58), the coexistence of these in cataract has not yet been reported and debated upon. Further, hypokalemia was significantly associated with hypertension in cataract patients. Even though the associa- tion of hypokalemia and hypertension has been previously reported (33,34), the common causes of hypertension with hypokalemia have been well established, which include essential hypertension with diuretic use, primary aldosteron- ism, Cushing’s syndrome, pheochromocytoma, renal vascular disease and malignant hypertension (59). Therefore, patients with coexistent hypertension and hypokalemia need to be evaluated further to establish the reason for the develop- ment of cataract. Conclusion In conclusion, serum glucose, sodium, potassium and calcium levels were identified as the potentially modifiable parameters deranged in cataract. In future, large-scale stud- ies to enhance the battery of biochemical markers and to establish cause and effect relationship between biochemical markers and cataract need to be done. Limitation of the study The sample size of the study is relatively modest. Biochemical markers in cataract10 © 2023 The Authors. Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb Disclosures Conflict of interest: The authors disclose that there are no financial or non-financial interests that are directly or indirectly related to the work submitted for publication. Financial support: The study was funded by Government Medical College Srinagar, Karan Nagar, Srinagar, Jammu & Kashmir, India, vide GMC/2022/17. Authors’/contributors’ list: Conceptualization: MSK, TR, SR; Data curation: MSK, SSA; Formal analysis: MSK, TR, SSA; Funding acqui- sition: TR, SM; Investigation: MSK, TR, SSA, RI; Methodology: RI; Project administration: SM, SR; Resources: SM; Software: MSK; Su- pervision: SM, SR; Validation: MSK, TR, SR; Visualization: MSK, RI; Writing—original draft: MSK, TR, RI; Writing-review and editing: MSK; Approval of final manuscript: all authors. References 1. Nizami AA, Gulani AC. Cataract. 2022 Jul 5. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan–. PubMed 2. Sayegh RR, Floyd RP, Ghanem RC, Azar DT. History of cata- ract surgery. In: Albert DM, Miller JW, Azar DT, Blodi BA, ed. Albert and Jakobiec’s principles and practice of ophthalmol- ogy. Philadelphia: Saunders 2008; 1,3. Online Accessed July 2022. 3. Cedrone C, Culasso F, Cesareo M, et al. Prevalence and inci- dence of age-related cataract in a population sample from Priverno, Italy. Ophthalmic Epidemiol. 1999 Jun;6(2):95-103. CrossRef PubMed 4. Types of Cataract. national Eye Institute. Online. 5. Milacic S. Risk of occupational radiation-induced cataract in medical workers. Med Lav. 2009;100(3):178-186. PubMed 6. Eye Exam: What to Expect. Online 7. Bourne RR, Stevens GA, White RA, et al; Vision Loss Expert Group. Causes of vision loss worldwide, 1990-2010: a sys- tematic analysis. Lancet Glob Health. 2013;1(6):e339-e349. CrossRef PubMed 8. Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012 May;96(5):614-618. CrossRef PubMed 9. Bunce GE, Kinoshita J, Horwitz J. Nutritional factors in cataract. Annu Rev Nutr. 1990;10(1):233-254. CrossRef PubMed 10. Minassian DC, Mehra V. 3.8 million blinded by cataract each year: projections from the first epidemiological study of incidence of cataract blindness in India. Br J Ophthalmol. 1990;74(6):341-343. CrossRef PubMed 11. Sperduto RD. Epidemiological aspects of age related cataract. In: Tasman W, Jaeger A, eds. Duane’s clinical ophthalmology. Lippincott Raven Publishers 2000; 12-14. 12. National programme for control of Blindness in India, Directorate General of Health Sciences. Rapid Assessment of Avoidable Blindness New Delhi Ministry of Health and Femen Welfare, Government of India. Online 13. Soudarssanane MB, Bansal RD. Prevalence of senile cataract in a rural population in Pondicherry. Indian J Community Med. 1985;10(3):175-179. Online Accessed July 2022. 14. Murthy GV, Gupta SK, Bachani D, Jose R, John N. Current esti- mates of blindness in India. Br J Ophthalmol. 2005;89(3):257- 260. CrossRef PubMed 15. Government of India. National survey on blindness and visual outcomes after cataract surgery. Dr. Rajendra Prasad Centre for Ophthalmic Sciences. New Delhi: All India Institute of Medical Sciences; 2001-2002. Online Accessed July 2022. 16. Sihota R, Tandon R. Parsons’ diseases of the eye, 23rd ed. Elsevier India 2019; 628. Online Accessed July 2022. 17. Garg P, Mullick R, Nigam B, Raj P. Risk factors associated with development of senile cataract. Ophthalmol J. 2020;5(0):17- 24. CrossRef 18. Klein BE, Klein R, Linton KL. Prevalence of age-related lens opacities in a population. The Beaver Dam Eye Study. Ophthalmology. 1992;99(4):546-552. CrossRef PubMed 19. Bron AJ, Vrensen GF, Koretz J, Maraini G, Harding JJ. The ageing lens. Ophthalmologica. 2000;214(1):86-104. CrossRef 20. Stanga PE, Boyd SR, Hamilton AMP. Ocular manifestations of diabetes mellitus. Curr Opin Ophthalmol. 1999;10(6):483-489. CrossRef PubMed 21. Rewatkar M, Muddeshwar MG, Lokhande M, Ghosk K. Electrolyte imbalance in eyes of Indian cataract patients. Ind Med Gaz. 2012;10:89-91. Online 22. Seeman E. Pathogenesis of bone fragility in women and men. Lancet. 2002;359(9320):1841-1850. CrossRef PubMed 23. Hightower KR, Hind D. Cytotoxic effects of calcium on sodium- potassium transport in the mammalian lens. Curr Eye Res. 1982-1983;2(4):239-246. CrossRef PubMed 24. Mukai K, Matsushima H, Ishii Y, Obara Y. [Effects of calcium on lens epithelial cells in rabbits]. Nippon Ganka Gakkai Zasshi. 2006;110(5):361-369. PubMed 25. Chandorkar AG, Bulakh PM, Albal MV. Electrolyte composi- tion in normal and cataractous lenses. Indian J Ophthalmol. 1980;28(3):135-138. PubMed 26. Bansal A, Amin H, Rekha R. Correlation of aqueous humor elec- trolytes with serum electrolytes in cataract patients. Indian J Ophthalmol. 2021;69(10):2675-2677. CrossRef PubMed 27. Gupta VB, Rajagopala M, Ravishankar B. Etiopathogenesis of cataract: an appraisal. Indian J Ophthalmol. 2014;62(2):103- 110. CrossRef PubMed 28. Asbell PA, Dualan I, Mindel J, Brocks D, Ahmad M, Epstein S. Age-related cataract. Lancet. 2005;365(9459):599-609. CrossRef PubMed 29. Zetterberg M, Celojevic D. Gender and cataract—the role of estrogen. Curr Eye Res. 2015;40(2):176-190. CrossRef PubMed 30. Ndong AK, van der Linden EL, Beune EJAJ, et al. Serum potas- sium concentration and its association with hypertension among Ghanaian migrants and non-migrants: the RODAM study. Atherosclerosis. 2022;342:36-43. CrossRef PubMed 31. Singh S, Pardhan S, Kulothungan V, et al. The prevalence and risk factors for cataract in rural and urban India. Indian J Ophthalmol. 2019;67(4):477-483. CrossRef PubMed 32. Lee SM, Lin SY, Li MJ, Liang RC. Possible mechanism of exacer- bating cataract formation in cataractous human lens capsules induced by systemic hypertension or glaucoma. Ophthalmic Res. 1997;29(2):83-90. CrossRef PubMed 33. Mukesh BN, Le A, Dimitrov PN, Ahmed S, Taylor HR, McCarty CA. Development of cataract and associated risk factors: the Visual Impairment Project. Arch Ophthalmol. 2006;124(1):79- 85. CrossRef PubMed 34. Cumming RG, Mitchell P. Medications and cataract. The Blue Mountains Eye Study. Ophthalmology. 1998;105(9):1751- 1758. CrossRef PubMed 35. Bamdad S, Shiraly R. Risk factors associated with cataracts in middle-aged people, an incidence-based case-control study in Shiraz, Iran. Shiraz E-Med J. 2019;20(9):1-7. CrossRef 36. Cataracts. John Hopkins Medicine. Online 37. Fekri Y, Ojaghi H, Moghadam TZ, Shargi A, Ranjbar A, Moghadam TZ. A study of morphology of cataract in surgery candidates in Ardabil: Iran. J Ardabil Univ Med Sci. 2020;20(1):127-136. Online Accessed July 2022. https://pubmed.ncbi.nlm.nih.gov/30969521 https://www.worldcat.org/title/489078723 https://doi.org/10.1076/opep.6.2.95.1562 https://pubmed.ncbi.nlm.nih.gov/10420209/ https://www.nei.nih.gov/learn-about-eye-health/eye-conditions-and-diseases/cataracts/types-cataract https://www.ncbi.nlm.nih.gov/pubmed/19601402 https://my.clevelandclinic.org/health/diagnostics/10738-eye-exam-what-to-expect https://doi.org/10.1016/S2214-109X(13)70113-X https://www.ncbi.nlm.nih.gov/pubmed/25104599 https://doi.org/10.1136/bjophthalmol-2011-300539 https://pubmed.ncbi.nlm.nih.gov/22133988/ https://doi.org/10.1146/annurev.nu.10.070190.001313 https://www.ncbi.nlm.nih.gov/pubmed/2200464 https://doi.org/10.1136/bjo.74.6.341 https://www.ncbi.nlm.nih.gov/pubmed/2378840 https://dghs.gov.in/content/1354_3_NationalProgrammeforControlofBlindnessVisual.aspx https://journals.lww.com/ijcm/Abstract/1985/10030/Prevalence_of_Senile_Cataract_in_a_Rural.6.aspx https://doi.org/10.1136/bjo.2004.056937 https://www.ncbi.nlm.nih.gov/pubmed/15722298 https://www.aiims.edu/images/depart/RPC/reports for web/1. NPCB National Blindness Survey 2001-02.pdf https://www.elsevier.com/books/parsons-diseases-of-the-eye/tandon/978-81-312-5415-8 https://doi.org/10.5603/OJ.2020.0005 https://doi.org/10.1016/S0161-6420(92)31934-7 https://www.ncbi.nlm.nih.gov/pubmed/1584573 https://doi.org/10.1159/000027475 https://doi.org/10.1097/00055735-199912000-00018 https://www.ncbi.nlm.nih.gov/pubmed/10662255 https://pesquisa.bvsalud.org/portal/resource/pt/sea-157387 https://doi.org/10.1016/S0140-6736(02)08706-8 https://www.ncbi.nlm.nih.gov/pubmed/12044392 https://doi.org/10.3109/02713688209011625 https://www.ncbi.nlm.nih.gov/pubmed/6295701 https://www.ncbi.nlm.nih.gov/pubmed/16764317 https://www.ncbi.nlm.nih.gov/pubmed/7216362 https://doi.org/10.4103/ijo.IJO_20_21 https://www.ncbi.nlm.nih.gov/pubmed/34571613 https://doi.org/10.4103/0301-4738.121141 https://pubmed.ncbi.nlm.nih.gov/24618482/ https://doi.org/10.1016/S0140-6736(05)70803-5 https://www.ncbi.nlm.nih.gov/pubmed/15708105 https://doi.org/10.3109/02713683.2014.898774 https://www.ncbi.nlm.nih.gov/pubmed/24987869 https://doi.org/10.1016/j.atherosclerosis.2021.12.006 https://www.ncbi.nlm.nih.gov/pubmed/34952692 https://doi.org/10.4103/ijo.IJO_1127_17 https://www.ncbi.nlm.nih.gov/pubmed/30900578 https://doi.org/10.1159/000268001 https://www.ncbi.nlm.nih.gov/pubmed/9154534 https://doi.org/10.1001/archopht.124.1.79 https://www.ncbi.nlm.nih.gov/pubmed/16401788 https://doi.org/10.1016/S0161-6420(98)99049-2 https://www.ncbi.nlm.nih.gov/pubmed/9754187 https://doi.org/10.5812/semj.86986 https://www.hopkinsmedicine.org/health/conditions-and-diseases/cataracts#:~:text=Cataracts%20cannot%20spread%20from%20one,Age%2Drelated%20cataracts https://jarums.arums.ac.ir/article-1-1779-en.html Rashid et al J Circ Biomark 2023; 12: 11 © 2023 The Authors. Published by AboutScience - www.aboutscience.eu 38. Malhotra C, Dhingra D, Nawani N, Chakma P, Jain AK. Phacoemulsification in posterior polar cataract: experi- ence from a tertiary eye care centre in North India. Indian J Ophthalmol. 2020;68(4):589-594. CrossRef PubMed 39. Garrigan H, Ifantides C, Prashanthi GS, Das AV. Biogeographical and altitudinal distribution of cataract: a nine-year experience using electronic medical record-driven big data analytics in India. Ophthalmic Epidemiol. 2021;5:392-399. CrossRef PubMed 40. Hassan H, Khaleel FM, Taee KA. Biochemical parameters determination for prognosis of retinal diseases and their rela- tionship to cataract, diabetes and hypertension patients in Ibn Al-Haytham Hospital in Baghdad-Iraq. Neuroquantology. 2021;19(5):43-44. CrossRef 41. Ipchi SP, Mahboub S, Hassanzadeh D, Safaeian AR, Rashidi MR, Zareh A. Relationship between Serum Na+, Ca++ and K+ lev- els, nutritional status and senile cataract formation. Pharm Sci. 2001;4:1-8. 42. The Italian-American Cataract Study Group. Risk factors for age-related cortical, nuclear, and posterior subcapsular cata- racts. Am J Epidemiol. 1991;133(6):541-553. PubMed 43. Mansoor A, Gul R, Malik TG, Khalil M, Alam R. Senile cata- ract patients; serum electrolytes and calcium. Prof Med J. 2015;22(9):1186-1191. CrossRef 44. Harahap J, Rania R. Cataracts Risk Factors and Comparison of Blood Glucose Levels in Diabetic and Non-Diabetic Patients towards the Occurrence of Cataracts. Open Access Maced J Med Sci. 2019 Oct 14;7(20):3359-3362. CrossRef PubMed PMCID: PMC6980819 45. Brian G, Taylor H. Cataract blindness—challenges for the 21st century. Bull World Health Organ. 2001;79(3):249-256. PubMed 46. Delcourt C, Carrière I, Ponton-Sanchez A, Lacroux A, Covacho MJ, Papoz L. Light exposure and the risk of cortical, nuclear, and posterior subcapsular cataracts: the Pathologies Oculaires Liées à l’Age (POLA) study. Arch Ophthalmol. 2000;118(3):385- 392. CrossRef PubMed 47. Kador PF, Wyman M, Oates PJ. Aldose reductase, ocular dia- betic complications and the development of topical Kinostat(®). Prog Retin Eye Res. 2016;54:1-29. CrossRef PubMed 48. Kinoshita JH. Mechanisms initiating cataract formation. Proctor Lecture. Invest Ophthalmol. 1974;13(10):713-724. PubMed 49. Mathur G, Pai V. Comparison of serum sodium and potassium levels in patients with senile cataract and age matched indi- viduals without cataract. Indian J Ophthalmol. 2013;3:44-47. CrossRef PubMed 50. Rajakrishnan PDR. An analysis of the levels of serum sodium and potassium ions in senile cataract patients. Univ J Pre Para Clin Sci. 2016;2:1-6. Online Accessed July 2022. 51. Miglior S, Marighi PE, Musicco M, Balestreri C, Nicolosi A, Orzalesi N. Risk factors for cortical, nuclear, posterior subcap- sular and mixed cataract: a case-control study. Ophthalmic Epidemiol. 1994;1(2):93-105. CrossRef PubMed 52. Donnelly CA, Seth J, Clayton RM, Phillips CI, Cuthbert J. Some plasma constituents correlate with human cataract location and nuclear colour. Ophthalmic Res. 1997;29(4):207-217. CrossRef PubMed 53. Duncan G, Bushell AR. Ion analyses of human cataractous lenses. Exp Eye Res. 1975;20(3):223-230. CrossRef PubMed 54. Chen CZ. [Analysis of 7 elements in the serum and lens of senile cataract patients]. Zhonghua Yan Ke Za Zhi. 1992;28(6):355- 357. PubMed 55. Daba KT, Weldemichael DK, Mulugeta GA. Bilateral hypocal- cemic cataract after total thyroidectomy in a young woman: case report. BMC Ophthalmol. 2019 21;19(1):233. CrossRef PubMed 56. Stolarz-Skrzypek K, Bednarski A, Czarnecka D, Kawecka-Jaszcz K, Staessen JA. Sodium and potassium and the pathogenesis of hypertension. Curr Hypertens Rep. 2013;15(2):122-130. CrossRef PubMed 57. Renzaho AMN, Burns C. Post-migration food habits of sub- Saharan African migrants in Victoria: a cross-sectional study. Nutr Diet. 2006;63(2):91-102. CrossRef 58. Elisaf M, Milionis H, Siamopoulos KC. Hypomagnesemic hypokalemia and hypocalcemia: clinical and laboratory charac- teristics. Miner Electrolyte Metab. 1997;23(2):105-112. PubMed 59. Abcar AC, Kujubu DA. Evaluation of hypertension with hypoka- lemia. Perm J. 2009;13(1):73-76. CrossRef PubMed https://doi.org/10.4103/ijo.IJO_932_19 https://www.ncbi.nlm.nih.gov/pubmed/32174575 https://doi.org/10.1080/09286586.2020.1849741 https://pubmed.ncbi.nlm.nih.gov/33213243/ https://doi.org/10.14704/nq.2021.19.5.NQ21047 https://www.ncbi.nlm.nih.gov/pubmed/1672483 https://doi.org/10.29309/TPMJ/2015.22.09.1133 https://doi.org/10.3889/oamjms.2019.422 https://www.ncbi.nlm.nih.gov/pubmed/32002050 https://www.ncbi.nlm.nih.gov/pubmed/11285671 https://doi.org/10.1001/archopht.118.3.385 https://www.ncbi.nlm.nih.gov/pubmed/10721962 https://doi.org/10.1016/j.preteyeres.2016.04.006 https://www.ncbi.nlm.nih.gov/pubmed/27102270 https://www.ncbi.nlm.nih.gov/pubmed/4278188 https://doi.org/10.4103/0301-4738.99837 https://www.ncbi.nlm.nih.gov/pubmed/23552357 http://ejournal-tnmgrmu.ac.in/index.php/para/article/view/591 https://doi.org/10.3109/09286589409052365 https://www.ncbi.nlm.nih.gov/pubmed/8790616 https://doi.org/10.1159/000268015 https://www.ncbi.nlm.nih.gov/pubmed/9261844 https://doi.org/10.1016/0014-4835(75)90136-0 https://www.ncbi.nlm.nih.gov/pubmed/1122997 https://www.ncbi.nlm.nih.gov/pubmed/1306472 https://doi.org/10.1186/s12886-019-1224-9 https://pubmed.ncbi.nlm.nih.gov/31752761/ https://doi.org/10.1007/s11906-013-0331-x https://www.ncbi.nlm.nih.gov/pubmed/23397214 https://doi.org/10.1111/j.1747-0080.2006.00055.x https://www.ncbi.nlm.nih.gov/pubmed/9252977 https://doi.org/10.7812/TPP/09.998 https://www.ncbi.nlm.nih.gov/pubmed/21373250