Decoding type 2 diabetes mellitus genetic risk variants in Pakistani Pashtun ethnic population using the nascent whole exome sequencing and MassARRAY genotyping: A case-control association study

Asif Jan; Zakiullah; Sajid Ali; Basir Muhammad; Amina Arshad; Yasar Shah; Haji Bahadur; Hamayun Khan; Fazli Khuda; Rani Akbar; Kiran Ijaz

doi:10.1371/journal.pone.0281070

. 2023 Jan 27;18(1):e0281070. doi: 10.1371/journal.pone.0281070

Decoding type 2 diabetes mellitus genetic risk variants in Pakistani Pashtun ethnic population using the nascent whole exome sequencing and MassARRAY genotyping: A case-control association study

Asif Jan ^1,^*,^#, Zakiullah ^1,^*,^#, Sajid Ali ^2,^‡, Basir Muhammad ^3,^‡, Amina Arshad ^4,^‡, Yasar Shah ^5,^‡, Haji Bahadur ^6,^‡, Hamayun Khan ^1,^‡, Fazli Khuda ^1,^‡, Rani Akbar ^5,^‡, Kiran Ijaz ^6,^‡

Editor: Giuseppe Novelli⁷

PMCID: PMC9882913 PMID: 36730981

Abstract

Genome-wide association studies have greatly increased the number of T2DM associated risk variants but most of them have focused on populations of European origin. There is scarcity of such studies in developing countries including Pakistan. High prevalence of T2DM in Pakistani population prompted us to design this study. We have devised a two stage (the discovery stage and validation stage) case-control study in Pashtun ethnic population in which 500 T2DM cases and controls each have been recruited to investigate T2DM genetic risk variants. In discovery stage Whole Exome Sequencing (WES) was used to identify and suggest T2DM pathogenic SNPs, based on SIFT and Polyphen scores; whereas in validation stage the selected variants were confirmed for T2DM association using MassARRAY genotyping and appropriate statistical tests. Results of the study showed the target positive association of rs1801282/PPARG (OR = 1.24, 95%Cl = 1.20–1.46, P = 0.010), rs745975/HNF4A (OR = 1.30, 95%Cl = 1.06–1.38, P = 0.004), rs806052/GLIS3 (OR = 1.32, 95%Cl = 1.07–1.66, P = 0.016), rs8192552/MTNR1B (OR = 1.53, 95%Cl = 0.56–1.95, P = 0.012) and rs1805097/IRS-2 (OR = 1.27, 95%Cl = 1.36–1.92, P = 0.045), with T2DM; whereas rs6415788/GLIS3, rs61788900/NOTCH2, rs61788901/NOTCH2 and rs11810554/NOTCH2 (P>0.05) showed no significant association. Identification of genetic risk factors/variants can be used in defining high risk subjects assessment, and disease prevention.

Introduction

Type 2 Diabetes Mellitus (T2DM) characterized by persistent hyperglycaemia is the most frequent subtype of diabetes accounting for around 90–95% of all diabetes cases [1, 2]. It arises from the combination of in-sufficient insulin secretion and excessive secretion of glucagon in a context of insulin resistance. These abnormalities results from alteration in number and/or function of β- and α-cells of pancreas [3, 4]. Loss of pancreatic β-cells in T2DM is believed to occur via apoptosis [5] and autophagy [6]. In addition to the common theme of beta cells failure and peripheral insulin resistance, complex interplay of genetic and non-genetic factors also contribute to the underlying pathophysiology of T2DM [7–9]. Molecular biology investigations have linked genetic variants in number of genes with T2DM. Some of these include PPARG [10], HNF4A [11], GLIS3 [12], MTNR1B [13], IRS-2 [14], NOTCH2 [15], WFS-1 [16], GCK [17], GCKR [18], NEUROD1 [19], HHEX [20], SLC30A8 [21], VEGFA [22] and CAP10 [23]. Other major players involved in the progression of T2DM includes obesity [24], sedentary lifestyle [25], poor diet [26] the metabolic [27] and environmental [28] factors. Identification of these risk factors greatly helps in diabetes assessment and prevention.

The global burden of diabetes has significantly increased and will continue to soar in next few decades [29]. According to International Diabetes Federation IDF Diabetes Atlas 10^th Edition; in the year 2021 approximately 537 million adults (of age 20–79 years) were estimated to have diabetes. This number is predicated to increase to 643 million by 2030 and 784 million by 2045. A high proportion (81.6%, 432 million) of peoples with diabetes live in low and middle income countries [30]. Prevalence of diabetes is not uniform; South Asian (people residing in China, India, Pakistan Sri Lanka, Bhutan, Nepal, and Maldives) are at high risk compared to other ancestral groups [31, 32]. In the year 2019 number of diabetic patients in Pakistan were 19.4 million in future it is predicated to rise to 34.4 million by 2030 and 37.1 million by 2045 [33]. Pakistan ranked 3^rd in diabetes prevalence race following China and India [30]. The main factors for marked increase in the incidence of diabetes in Pakistan includes high degree of urbanization and rapid transition in lifestyle [34, 35].

Recent genome wide association studies (GWAS) have greatly increased the number of T2DM associated risk variants but most of these studies have focused disproportionately individuals of European origin. There is scarcity of genomic research in developing countries including Pakistan. Increased prevalence of T2DM among Pakistanis and lack of genetic studies prompted us to design this case-control study. The study aimed to investigate Pashtun ethnic population of Khyber Pakhtunkhwa for T2DM risk variants using nascent technology of Whole Exome Sequencing (WES) and MassARRAY genotyping.

Materials and methods

Study subjects

A two stage (i.e. the discovery stage & the validation stage) case-control study have been designed. First Whole Exome Sequencing (WES) was performed to identify and suggest T2DM pathogenic variants in the target population. In the second stage the WES suggested pathogenic variants were confirmed for its association with T2DM using massARRAY genotyping. A total of 1000 individuals (healthy volunteers = 500 and T2DM cases = 500) of Pashtun ethnicity were recruited from seven districts (Peshawar, Mardan, Charsadda, Bannu, Kohat, Dir and swat) of Khyber Pakhtunkhwa, Pakistan for analysis. The cases were matched up with age, gender and ethnicity. Written informed consent was obtained from all the participants. For illiterate/un-educated patient’s understanding the informed consent form was read and explained in local Pashtu language and after patient’s agreement signed on his/her behalf by any of his/her relative/attendant. Patient’s detailed demographics and clinical parameter were noted on carefully designed proforma. The inclusion criteria for case group were (i) Diabetes diagnosed according to Internal Diabetes Federation (IDF) standard protocols, i.e., Fasting Blood Glucose (FBS) level greater than 126 mg/dL and random blood glucose (RBS) level greater than 200 mg/dL; (ii) Age between 30–80 years and (iii) Belonging from Pakistani Pashtun population. Exclusion criteria for case group were (i) Patients with chronic illness (presence of malignancies), recent severe infection (Hepatitis/Corona virus infection); and (ii) Patients of age not in range of 30–80 years. Whereas Controls were healthy volunteers from general population; age and gender wise matched with case group and fasting blood sugar level less than 100 mg/dL.

Ethics statement

The study was approved by the ethical committee Department of Pharmacy, University of Peshawar (Approval No. 907/PHAR). All the procedures were carried out in light of Helsinki declaration (1975).

Blood sampling

Three millilitre whole blood was collected by a trained nurse following aseptic procedures from the median cubital vein of study individuals in EDTA tubes (properly labelled), and was stored at -10°C.

DNA extraction and quantification

DNA was extracted from 200 micro litre (μl) whole blood samples of type 2 diabetes patients using Wiz-Prep DNA extraction kit (Wiz-Prep no. W54100) following manufacturer’s guidelines. Quantification was done using Invitrogen Qubit™3 and the final DNA concentration was adjusted to 5 ng/μL.

DNA samples pooling

DNA samples were pooled according to previously described protocol [36, 37]. Two DNA pools one of 500 T2DM cases and second of 500 control subjects were constructed. Each pool containing an equimolar amount of DNA (10ng) from each individual. DNA pooling simplifies sequencing process and reduces cost and time.

Whole exome sequencing

Whole Exome Sequencing (WES) was carried out at Genomic lab, Rehman Medical Institute (RMI), Hayatabad, Peshawar. Paired end libraries of pool samples were prepared using Illumina Nextera XT DNA library preparation kit. Quantified DNA libraries were sequenced using HiSeq2500 sequencing machine (Illumina, San Diego, CA, USA).

Bioinformatics analysis of WES data

We employed a custom-built in-house next generation sequencing bioinformatics pipeline to move from raw sequencing data to final variant call. FASTQ files produced by the Illumina HiSeq2500 were filtered to separate low quality reads (Q-score>30) using Trimmomatic software tool [38]. Filtered reads were then aligned to the reference genome (hg19/GRCh37) using a novel logarithmic tool the RAMICS [39]. Variant calling was performed using Genome Analysis Toolkit (GATK) and SAM tools [40, 41]. ANNOVAR was used for variants annotation [42]. The resulting annotated variant list generated by ANNOVAR was stored as Comma-Separated Values (CSV-file) having separate column for each annotation. The resultant CVS file was loaded/copied into an excel file for easy filtering, viewing and interpretation of data.

Filtration of WES data

WES generates huge data (>600 GB of data) handling of which is challenging and time consuming. To narrow down the list of variants of our interest the data was filtered as follows. Briefly the annotated file was first manually curated to shortlist putative variants. Non-synonymous, missense variants in exonic and splicing sites were retained, whereas Salient/synonymous variants were discarded (S1 Table). The resultant file was then filtered for selected genes previously reported for T2DM association (S2 Table). Next from list of selected T2DM associated genes we chose PPARG, HNF4A, GLIS3, MTNR1B, IRS-2, and NOTCH2 to be further investigated for T2DM susceptibility in the target population.

Confirmation of WES findings

WES suggested pathogenic variants were cross confirmed for its association with T2DM using Sequenom MassARRAY genotyping (Agena Bioscience, San Diego, CA). MassARRAY of Agena Biosciences easily genotype tens to hundreds of SNPs with great accuracy in short span of time and readily used in mutation detection and genotyping.

Statistical analysis

Statistical analysis was performed using IBM SPSS (Statistical Package for Social Sciences version 24). Key variables selected for analysis were gender, age, weight, geographical area (districts from where study subjects belongs), smoking, life style, exercise, diet, occupation, and variants reported in selected genes. All variant were tested for Hardy Weinberg equilibrium (HWE) using chi-square (χ²) test. The difference in distribution of Minor allele frequencies (MAFs) between diabetic patients and control volunteers were determined using χ² test. Association between Variants×T2DM were checked using binary logistic regression. A probability value of p < 0.05 was considered significant.

Results

Subject description

Details of socio-demographics and general characteristics of the study participants are given in Table 1. Prevalence of co-morbidities (i.e. hypertension, renal failure, hypercholesterolemia and retinopathy) was observed higher in diabetic cases compared to controls. Majority of the patients were physically inactive and were from urban areas of Khyber Pakhtunkhwa. Drug and diet compliance were recorded poor in study participants.

Table 1. Socio-demographic characteristics of cases and controls.

Variables	Case n(f)	Control n(f)	P-value
Gender			0.897
Male	358 (71.6%)	356 (71.2%)
Female	142 (28.4%)	144(28.8%)
Mean age (yrs)	57±12.40	57±13.43	0.951
Mean weight (kg)	61.64±6.07	59.55±8.32	0.801
Occupation			0.589
Labour	140 (28.0%)	119 (23.8%)
Govt servant	30 (6.0%)	40 (8.00%)
Business man	10 (2.00%)	08 (1.60%)
Farmer	20 (2.00%)	90 (18.0%)
House wife	130 (26.0%)	142 (28.4%)
Driver	80 (16.0%)	40(8.00%)
shopkeeper	90 (18.0%)	61(12.2%)
Geographical area (District)			0.439
Peshawar	150 (30.0%)	139 (27.8%)
Charsadda	70(14.00%)	82 (16.4%)
Swat	19(3.80%)	11 (2.20%)
Dir	11 (2.20%)	09 (1.80%)
Mardan	120(24.0%)	150 (30.0%)
Kohat	15 (3.00%)	08 (1.60%)
Bannu	25 (5.00%)	19 (3.80%)
Behlola	90(18.00%)	82(16.40%)
Family history of T2DM			0.02
Yes	475 (95.0%)	55 (11.00%)
No	25 (5.00%)	445(89.00%)
Exercise			0.11
Non-exercising	411 (82.2%)	370 (74.0%)
Walking	75 (15.0%)	98 (19.06%)
Jogging	09 (1.80%)	22(4.40%)
Gym/Sport	05 (1.00%)	10 (2.00%)
Smoking			0.62
Cigarette	113 (22.6%)	98 (19.06%)
Snuff	220 (44.0%)	240 (48.0%)
No-smoking	167 (33.4%)	162 (32.4%)
Diet control/compliance			0.43
Yes	290 (58.0%)	311 (62.2%)
No	210 (42.0%)	189 (37.8%)

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N = number; F = frequency; Yrs = years; Kg = kilogram.

WES results

Exome sequencing identified a total of n = 1248875 SNPs. Among these 691223 were heterozygous, 407572 homozygous, 74390 insertions and 99392 were deletions; 50280 were exonic SNPs, 7910 missense variants and 1987 variants were expressed in pancreas; A total 650 SNPs were reported pathogenic.

WES suggested T2DM associated SNPs

Exome Sequencing identified a total of n = 9 SNPs (rs1801282/PPARG, rs745975/HNF4A, rs6415788/GLIS3, rs806052/GLIS3, rs8192552/MTNR1B, rs1805097/IRS-2, rs61788900/NOTCH2, rs61788901/NOTCH2 and rs11810554/NOTCH2) in selected genes of our interest. Among these, 5 variants (rs1801282/PPARG, rs745975/HNF4A, rs806052/GLIS3, rs1805097/IRS-2 and rs8192552/MTNR1B) were suggested pathogenic and rest of 4 SNPs (rs6415788/GLIS3, rs61788900/NOTCH2, rs61788901/NOTCH2 and rs11810554/NOTCH2) were marked non-pathogenic by WES (Table 2).

Table 2. WES suggested diabetogenic and non-diabetogenic SNPs in the discovery stage.

Gene	Variant	SNP ID	Chr position	Variation type	Sift (score)	PolyPhen (score)	HGVSc	HGVSp
PPARG	C>C/G	rs1801282	3: 12393125	Missense_Variant	Deleterious (0.04)	Damaging (0.85)	NM_015869.4:c.34C>G	NP_056953.2:p.Pro12Ala
HNF4A	C>C/T	rs745975	20:44406053	Splice variant	Deleterious (0.0)	Damaging (0.97)	NM_000457.4:c.116-5C>T	------
GLIS3	G>G/T	rs6415788	9:4118111	missense_variant	Tolerated (0.91)	Benign (0)	NM_001042413.1:c.1367C>A	NP_001035878.1:p.Pro456Gln
GLIS3	A>G/G	rs806052	9:4118208	missense_variant	Deleterious (0.02)	Possibly damaging (0.15)	NM_001042413.1:c.1270T>C	NP_001035878.1:p.Ser424Pro
MTNR1B	G>G/A	rs8192552	11: 92702962	Missense_Variant	Deleterious (0.01)	Damaging (0.71)	NM_005959.3:c.71G>A	NP_005950.1:p.Gly24Glu
IRS2	C>C/T	rs1805097	13:11043523	missense_variant	Deleterious (0.0)	Damaging (0.91)	NM_003749.2:c.3170G>A	NP_003740.2:p.Gly1057Asp
NOTCH2	T>T/C	rs61788900	1:120029924	Missense_Variant	Tolerated (0.06)	Benign (0.028)	NM_024408.3:c.137A>G	NP_077719.2:p.Asn46Ser
NOTCH2	C>C/T	rs61788901	1:120572572	Missense_Variant	Tolerated (0.18)	Benign (0.013)	NM_024408.3:c.112G>A	NP_077719.2:p.Glu38Lys
NOTCH2	G>G/C	rs11810554	1:120611964	Missense_Variant	Tolerated (0.09)	Benign (0.12)	NM_024408.3:c.57C>G	NP_077719.2:p.Cys19Trp

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Abbreviations: chr: chromosome; HGVS: human genome association variation; HGVSc: the HGVS coding sequence name; HGVSp: the HGVS protein sequence. Het: Heterozygous; Homo: homozygous.

Validation/confirmation of WES suggested diabetogenic SNPs

WES generates accurate and reliable results however possibility of false negative and false positive results exists. In order to validate and reduce chances false-negative and false-positive identification rates; all the selected WES identified (n = 9) SNPs were genotyped using MassARRAY and association analysis was performed using appropriate statistical tests. Genotyping and association analysis confirmed strong association (P<0.05) of WES suggested SNPs with T2DM in the study population. WES suggested pathogenic SNPs (n = 5) showed marked difference in the distribution of minor allele frequencies (MAFs) between T2DM patients and controls. Risk alleles burden was observed higher in T2DM patients compare to controls (Table 3).

Table 3. Confirmation of WES suggested diabetogenic variants in the validation stage.

Gene	SNP	Alleles (major/minor)	MAF (controls)	MAF (cases)	OR (95% CI)	P-value
PPARG	rs1801282	C/G	0.21	0.25	1.24 (1.20–1.46)	0.010
HNF4A	rs745975	C/T	0.30	0.36	1.19 (1.06–1.38)	0.004
GLIS3	rs6415788	G/T	0.17	0.19	1.17 (0.87–1.57)	0.124
GLIS3	rs806052	A/G	0.10	0.14	1.32 (1.07–1.66)	0.016
MTNR1B	rs8192552	G/A	0.23	0.27	1.53 (0.56–1.95)	0.012
IRS2	rs1805097	C/T	0.30	0.35	1.27 (1.36–1.92)	0.045
NOTCH2	rs61788900	T/C	0.40	0.39	1.09 (0.97–1.22)	0.242
NOTCH2	rs61788901	C/T	0.22	0.20	1.15 (0.87–1.53)	0.191
NOTCH2	rs11810554	G/C	0.30	0.29	1.07 (0.93–1.22)	0.235

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Discussion

It is hypothesized that genetic makeup of Pakistani Pashtun population is different from other sub-populations and has unique cultural practices, social values, life style and behaviours, that make this population suitable for genomic studies. No previous comprehensive genomic study as of the present exists in this ethnic group. We confirmed positive association of genetic variations in PPARG (rs1801282), HNF4A (rs745975), GLIS3 (rs806052), IRS-2 (rs1805097) and MTNR1B (rs8192552) with T2DM. Whereas genetic variants GLIS3 (rs6415788) and NOTCH2 (rs61788900, rs61788901 and rs11810554) showed no noticeable association.

The Peroxisome Proliferator Activated Receptor Gamma (PPARG) is an important transcription factors that has a key role in regulating adipocyte differentiation and controlling glucose and lipid haemostasis [43]. Genome Wide Association Studies (GWAS) in different ancestries reported that single nucleotide polymorphisms in several candidate genes including PPARG increases risk of developing T2DM [44, 45]. Among several T2DM associated risk variants one variant extensively studied in different epidemiological study is rs1801282/ PPARG [46]. The present study for the first time in Pakistani Pashtun population reported the association of rs1801282/PPARG (C>G) with T2DM. WES marked the variant (also known as Pro12Ala) as deleterious and damaging based on SIFT and PolyPhen (0.0 and 0.85) score; Whereas; genotyping by massARRAY confirmed positive association (P = 0.010). Our study findings were compatible with result outcomes of a number of previously genomic studies conducted in different ethnic populations [47–50].

HNF4A in beta cells of pancreas regulates expression of genes involved in insulin secretion and glucose metabolism. Polymorphisms in HNF4A affects normal glucose metabolism leading to T2DM [51, 52]. The SNP rs745975 in or near HNF4A gene in the study population showed strong association (P = 0.004). In concordance to our study findings a large scale association study conducted in Japanese Population also marked rs745975 polymorphism as potential risk factor for T2DM [53]. Likewise variant rs806052/ GLIS3 showed positive association (P = 0.016) with T2DM in the study population. In contrast to our findings a study conducted in Caucasian population doesn’t detect any association of rs806052/ GLIS3 with T2DM the possible variation in results are due to population heterogeneity [54]. Similarly we confirmed the association of rs1805097/IRS-2 (P = 0.045) with T2DM in the study population. Previously a case-control study conducted in Bangladeshi population consist of total n = 231 unrelated Bangladeshi (T2DM cases n = 123 and controls n = 108) reported that the variant rs1805097 in IRS-2 has significantly associated with T2DM in particularly female patients [55]. It is hypothesized that this variant impairs glucose haemostasis leading to T2DM [56, 57]. Moreover we also reported a pathogenic, non-synonymous, heterozygous variant (rs8192552) in MTNR1B gene. A similar study case-control study as of ours in Turkish population confirmed the association of variant rs8192552/MTBR1B with obesity and related co-morbidities like Insulin Resistance and hypercholesterolemia [58] The reported variant impair normal blood glucose level causing T2DM [59]. We could not confirm association between rs6415788/GLIS3, rs61788900/NOTCH2, rs61788901/NOTCH2, and rs11810554/NOTCH2 with T2DM in the target population. Contrary to our study findings genetic alterations in GLIS3 and NOTCH2 confer risk for T2DM in Europeans [60, 61]. The conflicting results are due to population genetic differences.

Conclusion

The present two stage case-control study, using Exome Sequencing and follow-up MassARRAY genotyping of selected genes reported association of polymorphism in PPARG, HNF4A, GLIS3, MTNR1B, IRS-2, and NOTCH2 with T2DM in Pashtun ethnic population for the first time. The study identified and confirmed potential T2DM causing risk variants in the aforementioned genes. In view of growing number T2DM cases in Pashtun ethnic population it is recommended that similar studies be conducted on other risk variants for T2DM, which will ultimately help in developing risk variant panel genes for screening and identification of genetically susceptible individuals. It will help in devising life style modification and other such strategies that will reduce burden of this fatal and costly disease.

Supporting information

S1 Table. Complete list of putative non-synonymous, missense variants.

(RAR)

Click here for additional data file.^{(36MB, rar)}

S2 Table. List of selected genes, previously associated with type 2 diabetes mellitus.

(XLSX)

Click here for additional data file.^{(51.8KB, xlsx)}

Acknowledgments

we are thankful to control subjects (volunteers) and diabetic patients for agreeing to participate in this study. We are grateful to Dr. Johar Ali, head of Centre of Genomics, Rehman Medical Institute (RMI), Hayatabad, Peshawar and Dr. Muhammad Hussain Afridi, consultant endocrinologist of Hayatabad Teaching Hospital (HMC) Peshawar for their kind collaboration and helping us in collecting patient’s demographics and blood samples. We also thank Syed Adnan Ali Haider Statistical Assistant at for at the Centre of Genomics, Rehman Medical Institute his kind efforts in bioinformatics analysis of data.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This research project was approved and supported financially by Higher Education Research Department, Government of Khyber Pakhtunkhwa Pakistan (Fund No. PMU1-22/HEREF/2014-15/ VolIV/3408) for laboratory materials and reagent kits. However, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0281070.r001

Decision Letter 0

Giuseppe Novelli

5 Jan 2023

PONE-D-22-30913Decoding Type 2 Diabetes Mellitus Genetic Risk Variants in Pakistani Pashtun Ethnic Population Using the Nascent Whole Exome Sequencing and MassARRAY Genotyping: A Seven Districts Based Case-Control Association Study.PLOS ONE

Dear Dr. Jan,

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Reviewer #3: Yes

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Reviewer #1: N/A

Reviewer #2: I Don't Know

Reviewer #3: Yes

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Reviewer #1: The work presents a study on selected genetic variants and their association to the risk of T2DM in a sample of the Pakistani population, with the aim of cut the information gap with other populations already studied. Given the well-known complexity of the genetic mechanisms associated with T2DM, the work details are insufficient. It is necessary: to motivate the reasons for the choice of the selected variants leading to the final list, to compare thi list with the variants of other meta-analyses on different ethnic groups, to avoid the use of the term "pathogenetic" referring to risk variants, to distinguish heterozygous and homozygous variants with relative individual/group clinical effects, to present exhaustive tables with numbers of subjects for each variant (do not refer the reader to S1), to analyze the combined genotypes of the variants among individuals/groups to evaluate synergic effects.

Reviewer #2: The aim of this study is to evaluate in the Pakistan population T2DM risk variants comparing two populations, 500 T2DM (Type 2 Diabetes Mellitus) cases and 500 controls. In discovery stage, Whole Exome Sequencing (WES) was used to identify and suggest T2DM pathogenic SNPs; in the validation stage, the pathogenic SNPs identified were confirmed for T2DM association using MassARRAY genotyping and appropriate statistical tests. They found 5 SNPs associated with an increased risk of T2DM, whereas 3 SNPs were not associated with an increased risk.

I suggest to the authors to implement the English language, there are a lot of grammatic mistakes, long sentences, missing commas, words not really English.

- Page 3 beginning: repeated “it is believed”

- Page 3 at the end: are living with diabetes

- Page 4 pakistan…india

And others!

I suggest explaining the age of controls, not only median value and SD (my idea is that they are not affected by diabetes because too young??) and the specific values of normal blood glucose, in the guidelines they are not specified. Is there someone with IGT and IFG? Remember that blood glucose from 110 to 125 mg/dl is associated with IFG, but you say that controls have blood glucose from 70 to 120 mg/dl.

ANNOVAR or ANNOVER? (page 6)

Sailent variants? (page 7)

Wes results: What are 650 pathogenic SNPs identified? In what genes? The paragraph of WES results is confused.

I should suggest explaining why you considered few genes (only 5) instead of the group of genes well know associated with T2DM cited in the introduction and why and how you have reduced the number of Pathogenic SNPs from 650 to 5.

Because your study is not showing new data (except you have confirmed that in pakistani population you can find the same variants than in other population), you can propose new genes because the SNPs you have identified are in genes well known in other populations

Reviewer #3: Dear Editor,

the article by Asif Jan et al. entitled " Decoding Type 2 Diabetes Mellitus Genetic Risk Variants in Pakistani Pashtun Ethnic Population Using the Nascent Whole Exome Sequencing and MassARRAY Genotyping: A Seven Districts Based Case-Control Association Study" is interesting study, on an ethnic group, Pakistani Pashtun, not yet analyzed for the genetic risk score in Diabetes Mellitus. In the last decades, this ethnic group had a significant increase in the prevalence and incidence of type 2 diabetes mellitus.

The experimental design and the statistical evaluation are well conducted.

However, I need clarification:

1. The reason why the analysis was conducted by using Whole Exome Sequencing and then, only the polymorphisms/SNPs reported in table S1 were analyzed. Probably a specific chip could be created for the reported SNPs. I think that some potential data are missing, not evaluable and quantifiable using this approach.

2. It is possible to obtain, beyond the significance for the association between the identified SNPs and Type 2 Diabetes Mellitus, the increased risk of developing Type 2 Diabetes Mellitus in the population under analysis due to the polymorphisms found.

3. It might be nice to know the association percentage of two or more polymorphisms in the population examined.

Kind regards,

**********

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Reviewer #3: No

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PLoS One. 2023 Jan 27;18(1):e0281070. doi: 10.1371/journal.pone.0281070.r002

Author response to Decision Letter 0

12 Jan 2023

EXPLANATORY RESPONSE LETTER

We appreciate you and the reviewers for your precious time in reviewing our paper and providing valuable comments. It was your valuable and insightful comments that led to possible improvements in the current version. The authors have carefully considered the comments and tried our best to address every one of them. We hope the manuscript after careful revisions meet your high standards. The authors welcome further constructive comments if any. Below we provide the point-by-point responses;

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https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: The needful done and revised as per guidelines

2. Thank you for stating the following financial disclosure:

"This research project was approved and supported financially by Higher Education Research Department, Government of Khyber Pakhtunkhwa Pakistan (Fund No. PMU1-22/HEREF/2014-15/ VolIV/3408)."

Response: The needful done as required

3. Thank you for stating the following in your Competing Interests section:

"No competing interest to declare"Please complete your Competing Interests on the online submission form to state any Competing Interests. If you have no competing interests, please state "The authors have declared that no competing interests exist.", as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now This information should be included in your cover letter; we will change the online submission form on your behalf.

Response : The needful done as required

Response: The needful done as required

Comments to Authors

1. Is the manuscript technically sound, and do the data support the conclusions?

2. Reviewer #1: Partly

3. Reviewer #2: Partly

4. Reviewer #3: Yes

Response: The abstract and conclusion have been revised and made more coherent and representative of the results. Conclusion is made more clear and explicit and rephrased completely.Hope it will be now upto the mark and satisfaction of the reviewer.

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: I Don't Know

Reviewer #3: Yes

Response: Yes performed appropriately and rigorously; it's already approved by reviewer.

3. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes

Response: Detailed Manuscript with supplementary data was provided earlier. However as per journal requirement and reviewer suggestion this time (in revised manuscript) exhaustive supplementary table S1 and S2 containing A to Z information is provided. Beside this we have more than 600 GB project data some are machine readable files (like FAST-Q, VCF files) some are in excel and other are TSV files. However relevant data (S1 and S2 tables) are provided as supporting information with revised manuscript. And there is no restriction on our data sharing.

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Response: The manuscript has been revised thoroughly. Abstract, introduction, discussion and conclusion made more comprehensive, coherent and language has been improved significantly. Changes can be seen in track changes option draft provided.Changes and improvements identified by reviewers in draft have been incorporated.

5. Review Comments to the Author

Response: Thank you very much for your previous comments that helped us to improve and polish this manuscript.

Yes; we agree with the reviewer the present study intends to understand the 1). Shared genetic basis of T2DM and 2) possible heterogeneity between Pakistani Pashtun and other populations.

Pashtun population was selected because this population is 1). Understudied 2). Genetically unique. We attempted to fill genetic information gap as enough studies are carried out in European population but not in the present population.

As per reviewer suggestions; this time we provided detailed/ exhaustive supplementary table. That includes all relevant data mentioned by the respected reviewer in his comments (i.e. type of variant : heterozygous or homozygous, chromosome number, read depth, amino acid alterations, Minor allele frequency (MAF), and MAFs status in other ethnic population)

As for variant selection is concern.

We prefer variants that were

1) exonic

2) Missense

3) Non-synonymous

4) Insertions/deletion

5) Variants in core genes previously reported in European decent but not in our population to highlight the concept of shared genetic and heterogeneity.

Hope it satisfies the reviewers. Any further suggestion (if any) are welcomed and appreciated.

I suggest to the authors to implement the English language, there are a lot of grammatic mistakes, long sentences, missing commas, words not really English. Page 3 beginning: repeated “it is believed” Page 3 at the end: are living with diabetes Page 4pakistan…india

Andothers!

ANNOVAR or ANNOVER? (page 6)

Sailent variants? (page 7)

Wes results: What are 650 pathogenic SNPs identified? In what genes? The paragraph of WES results is confused.

Response: Thank you for pointing out English and grammatical mistakes; all spelling and grammatical errors pointed out by your good self have been corrected throughout the manuscript (page 1-25). Also repeated words are removed. Moreover while recruiting study participants (controls and cases) it was well assured that they are age, gender and ethnicity matched.

Normal blood glucose range is modified as per IDF diagnosis criteria for diabetes.( IDF-T2D-CPR-2017-print.pdf)

Thank for thorough review of our manuscript as your good-self pinpoint mistakes like ANNOVAR or ANNOVER? The correct is ANNOVAR. The name is corrected in the revised manuscript.

WES results/statistics reflects: complete list of variants identified. We simplified the list further: filter out the list that out that complete list who much is missense, who much non-synonymous, how much is insertions/deletions how much are benign and how much are disease causing or pathogenic. When we filter our list for pathogenic so the count was 650. Now these 650 variants are in a number of genes. We reporting these genes in sequences some are reported in this manuscript and remaining will be reported in other articles which are in pipeline and hopefully that will be submitted to the same journal.

In this study we have selected some prominent gene variants for further assay and analysis as identified by WES results.

Ideally this research study first of its kind intended to identify and confirms daibetogenic in Pashtun population. By comparing this data with other ethnic population research data it seems a simple validation study. However even such studies as of present; needed to assess the genetic risk among Pakistanis are lacking. To fill the genetic information gap btw European and Pakistan we design this study. The present study reported variants which are common in our cohort and European cohort representing share genetic basis of T2DM and reported some other variants which are responsible for T2DM in European cohort but not in present population. Which represent the term heterogeneity.

Hope it satisfy your goodself.

Reviewer #3:

DearEditor,

The experimental design and the statistical evaluation are well conducted.

However, I need clarification:

3. It might be nice to know the association percentage of two or more polymorphisms in the population examined.

Response: Thanks for valuation suggestions and critical analysis.

1: Actually WES has been performed on pools of DNA as described in methodology section and an overall picture of the variants that are present is obtained. We have around 30 GB data generated through this and are analysing and publishing from various aspects.

In current study we have validated some of the associated gene variants, previousely reported and also suggested and supported by our WES results. Validation have shown association of some variants and non association of some variants associated in other ethnicities.

2: Yes we agree and carried out a whole picture irrespective of the previousely reported variants and also some other aspects have been published by our group somewhere else.

Current study is limited to some selected gene variants that we considered more important to be reported here.

3: Your suggestion is valuable. However we think that the current results of the study are sufficient to infere and get the conclusion drawn in this manuscript.

Hope it satisfies the reviewers. Further suggestion (if any) is appreciated.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(38KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0281070.r003

Decision Letter 1

Giuseppe Novelli

16 Jan 2023

Decoding Type 2 Diabetes Mellitus Genetic Risk Variants in Pakistani Pashtun Ethnic Population Using the Nascent Whole Exome Sequencing and MassARRAY Genotyping: A Case-Control Association Study.

PONE-D-22-30913R1

Dear Dr. Jan,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0281070.r004

Acceptance letter

Giuseppe Novelli

19 Jan 2023

PONE-D-22-30913R1

Decoding Type 2 Diabetes Mellitus genetic risk variants in Pakistani Pashtun ethnic population using the nascent Whole Exome Sequencing and MassARRAY genotyping: A case-control association study.

Dear Dr. Jan:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Complete list of putative non-synonymous, missense variants.

(RAR)

Click here for additional data file.^{(36MB, rar)}

S2 Table. List of selected genes, previously associated with type 2 diabetes mellitus.

(XLSX)

Click here for additional data file.^{(51.8KB, xlsx)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(38KB, docx)}

Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

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PERMALINK

Decoding type 2 diabetes mellitus genetic risk variants in Pakistani Pashtun ethnic population using the nascent whole exome sequencing and MassARRAY genotyping: A case-control association study

Asif Jan

Zakiullah

Sajid Ali

Basir Muhammad

Amina Arshad

Yasar Shah

Haji Bahadur

Hamayun Khan

Fazli Khuda

Rani Akbar

Kiran Ijaz

Roles

Abstract

Introduction

Materials and methods

Study subjects

Ethics statement

Blood sampling

DNA extraction and quantification

DNA samples pooling

Whole exome sequencing

Bioinformatics analysis of WES data

Filtration of WES data

Confirmation of WES findings

Statistical analysis

Results

Subject description

Table 1. Socio-demographic characteristics of cases and controls.

WES results

WES suggested T2DM associated SNPs

Table 2. WES suggested diabetogenic and non-diabetogenic SNPs in the discovery stage.

Validation/confirmation of WES suggested diabetogenic SNPs

Table 3. Confirmation of WES suggested diabetogenic variants in the validation stage.

Discussion

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Giuseppe Novelli

Roles

Author response to Decision Letter 0

Decision Letter 1

Giuseppe Novelli

Roles

Acceptance letter

Giuseppe Novelli

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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