Medicine
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Item Validation of the World Health Organization/ International Society of Hypertension (WHO/ISH) cardiovascular risk predictions in Sri Lankans based on findings from a prospective cohort study(Public Library of Science, 2021) Thulani, U.B.; Mettananda, K.C.D.; Warnakulasuriya, D.T.D.; Peiris, T.S.G.; Kasturiratne, K.T.A.A.; Ranawaka, U.K.; Chakrewarthy, S.; Dassanayake, A.S.; Kurukulasooriya, S.A.F.; Niriella, M.A.; de Silva, S.T.; Pathmeswaran, A.; Kato, N.; de Silva, H.J.; Wickremasinghe, A.R.INTRODUCTION AND OBJECTIVES: There are no cardiovascular (CV) risk prediction models for Sri Lankans. Different risk prediction models not validated for Sri Lankans are being used to predict CV risk of Sri Lankans. We validated the WHO/ISH (SEAR-B) risk prediction charts prospectively in a population-based cohort of Sri Lankans. METHOD: We selected 40-64 year-old participants from the Ragama Medical Officer of Health (MOH) area in 2007 by stratified random sampling and followed them up for 10 years. Ten-year risk predictions of a fatal/non-fatal cardiovascular event (CVE) in 2007 were calculated using WHO/ISH (SEAR-B) charts with and without cholesterol. The CVEs that occurred from 2007-2017 were ascertained. Risk predictions in 2007 were validated against observed CVEs in 2017. RESULTS: Of 2517 participants, the mean age was 53.7 year (SD: 6.7) and 1132 (45%) were males. Using WHO/ISH chart with cholesterol, the percentages of subjects with a 10-year CV risk <10%, 10-19%, 20%-29%, 30-39%, ≥40% were 80.7%, 9.9%, 3.8%, 2.5% and 3.1%, respectively. 142 non-fatal and 73 fatal CVEs were observed during follow-up. Among the cohort, 9.4% were predicted of having a CV risk ≥20% and 8.6% CVEs were observed in the risk category. CVEs were within the predictions of WHO/ISH charts with and without cholesterol in both high (≥20%) and low(<20%) risk males, but only in low(<20%) risk females. The predictions of WHO/ISH charts, with-and without-cholesterol were in agreement in 81% of subjects (ĸ = 0.429; p<0.001). CONCLUSIONS: WHO/ISH (SEAR B) risk prediction charts with-and without-cholesterol may be used in Sri Lanka. Risk charts are more predictive in males than in females and for lower-risk categories. The predictions when stratifying into 2 categories, low risk (<20%) and high risk (≥20%), are more appropriate in clinical practice.Item Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries(Public Library of Science, 2018) Feitosa, M.F.; Kraja, A.T.; Chasman, D.I.; Sung, Y.J.; Winkler, T.W.; Ntalla, I.; Guo, X.; Franceschini, N.; Cheng, C.Y.; Sim, X.; Vojinovic, D.; Marten, J.; Musani, S.K.; Li, C.; Bentley, A.R.; Brown, M.R.; Scwander, K.; Richard, M.A.; Noordam, R.; Aschard, H.; Bartz, T.M.; Bielak, L.F.; Dorajoo, R.; Fishaer, V.; Hartwig, F.P.; Horimoto, A.R.V.R.; Lohman, K.K.; Manning, A.K.; Rankinen, T.; Smith, A.V.; Tajiddin, S.M.; Wojczynski, M.K.; Alver, M.; Boissel, M.; Cai, Q.; Campbell, A.; Chai, J.F.; Chen, X.; Divers, J.; Gao, C.; Goel, A.; Hagemeijer, Y.; Harris, S.E.; He, M.; Hsu, F.C.; Jackson, A.U.; Kahonen, M.; Kasturiratne, A.; Komulainen, P.; Kuhnel, B.; Laguzzi, F.; Luan, J.; Matoba, N.; Nolte, I.M.; Padmanabhan, S.; Riaz, M.; Rueedi, R.; Robino, A.; Said, M.A.; Scott, R.A.; Soffer, T.; Stancakova, A.; Takeuchi, F.; Tayo, B.O.; van de Most, P.J.; Varga, T.V.; Vitart, V.; Wang, Y.; Ware, E.B.; Warren, H.R.; Weiss, S.; Wen, W.; Yanek, L.R.; Zhang, W.; Zhao, J.H.; Afaq, S.; Amin, N.; Amini, M.; Arking, D.E.; Aung, T.; Boerwinkle, E.; Borecki, I.; Broecki, I.; Broeckel, U.; Brown, M.; Brumat, M.; Burke, G.L.; Canouil, M.; Chakravarthi, A.; Charumathi, S.; Ida Chen, Y.D.; Connel, J.M.; Correa, A.; de Las Fuentes, L.; de Mutsert, R.; de Silva, H.J.; Deng, X.; Ding, J.; Duan, Q.; Eaton, C.B.; Ehret, G.; Eppinga, R.N.; Evangelou, E.; Faul, J.D.; Felix, S.B.; Forouhi, N.G.; Forrester, T.; Franco, O.H.; Friedlander, Y.; Gandin, I.; Gao, H.; Ghanbari, M.; Gigante, B.; Gu, C.C.; Gu, D.; Hagenaars, S.P.; Halmans, G.; Harris, T.B.; He, J.; Heikkinen, S.; Heng, C.K.; Hirata, M.; Howard, B.V.; Ikram, M.A.; InterAct Consortium; John, U.; Katsuya, T.; Lakka, T.A.; Langefeld, C.D.; Langenberg, C.; Launer, L.J.; Lehne, B.; Lewis, C.E.; Li, Y.; Lin, S.; Lin, U.; Liu, J.; Liu, J.; Loh, M.; Louie, T.; Magi, R.; McKenzie, C.A.; Meitinger, T.; Metspalu, A.; Milaneschi, Y.; Milani, L.; mohlke, K.L.; Momozawa, Y.; Nalls, M.A.; Nelson, C.P.; Sotoodehnia, N.; Norris, J.M.; O'Connel, J.R.; Palmer, N.D.; Perls, T.; Pedersen, N.L.; Peters, A.; Peyser, P.A.; Poulter, N.; Raffel, L.J.; Raitakari, O.T.; Roll, K.; Rose, L.M.; Rosendaal, F.R.; Rotter, J.I.; Schimidit, C.O.; Schreiner, P.J.; Schupf, N.; Scott, W.R.; Sever, P.S.; Shi, Y.; Sidney, S.; Sims, M.; Sitlani, C.M.; Smith, J.A.; Snieder, H.; Starr, J.M.; Strauch, K.; Stringham, H.M.; Tan, N.Y.Q.; Tang, H.; Taylor, K.D.; Teo, Y.Y.; Tham, Y.C.; Turner, S.C.; Uitterlinden, A.G.; Vollenweider, P.; Waldenberger, M.; Wang, L.; Wang, Y.X.; Wei, W.B.; Williams, C.; Yao, J.; Yuan, J.M.; Zhao, W.; Zonderman, A.B.; Becker, D.M.; Boehnke, M.; Bowden, D.W.; Chambers, J.C.; Deary, I.J.; Esco, T.; Farall, M.; Frankd, P.W.; Freedman, B.I.; Froguel, P.; Gasparini, P.; Gieger, C.; Jonas, J.B.; Kamatani, Y.; Kato, N.; Kooner, J.S.; Kutalik, Z.; Laakso, M.; Laurie, C.C.; Leander, K.; Lehtimaki, T.; Study, L.C.; Magnusson, P.K.E.; Olderhinkel, A.J.; Penninx, B.W.J.H.; Polasek, O.; Porteous, D.J.; Rauramaa, R.; Ssamani, N.J.; Scott, J.; Shu, X.O.; van der Harst, P.; Wagenknecht, L.E.; Wareham, N.J.; Watkins, H.; Weir, D.R.; Wickremasinghe, A.R.; Wu, T.; Zheng, W.; Bouchard, C.; Christensen, K.; Evans, M.K.; Gudnason, V.; Horta, B.L.; Kardia, S.L.R.; Liu, Y.; Pereira, A.C.; Psaty, B.M.; Ridker, P.M.; van Dam, R.M.; Gauderman, W.J.; Zhu, X.; Mook-Kanamori, D.O.; Fornage, M.; Rotimi, C.N.; Cupples, L.A.; Kelly, T.N.; Fox, E.R.; Hayward, C.; van Duijn, C.M.; Tai, E.S.; Wong, T.Y.; Kooperberg, C.; Palmas, W.; Rice, K.; Morrison, A.C.; Elliott, P.; Caulfield, M.J.; Munroe, P.B.; Rao, D.C.; Province, M.A.; Levy, D.Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertensionItem Patterns of alcohol use and occurrence of alcoholic fatty liver disease: a prospective, community cohort, 7-year follow-up study(Sri Lanka Medical Association, 2017) Niriella, M.A.; de Silva, S.T.; Kasturiratne, A.; Perera, K.R.; Subasinghe, S.K.C.E.; Kodisinghe, S.K.; Piyaratna, T.A.C.L.; Vithiya, K.; Dassanayake, A.S.; de Silva, A.P.; Pathmeswaran, A.; Wickremasinghe, A.R.; Kato, N.; de Silva, H.J.INTRODUCTION & OBJECTIVES: Data is limited on alcoholic fatty liver disease (AFLD). We investigated patterns of alcohol use and AFLD, among urban, adult, Sri Lankans. METHODS: Study population (selected by age-stratified random sampling from Ragama MOH-area) was screened initially in 2007 (35-64 years) and re-evaluated in 2014. On both occasions they were assessed by structured-interview, anthropometric measurements, liver ultrasound, biochemical and serological tests. AFLD was diagnosed on ultrasound criteria, unsafe alcohol consumption (Asian standards: males>14units, females>7units per week) and absence of hepatitis B/C markers. Controls were individuals with unsafe alcohol consumption, but had no ultrasound criteria of AFLD. Case-control genetic-association for PNPLA3 (rs738409) polymorphism for AFLD was performed. RESULTS: A total of 2983/3012 (99%) had complete data. 272/2983(9.1%) were unsafe-drinkers [males- 70; mean-age 51.9 (SD-8.0) years]. 86/2983 (2.9%) of the cohort and 86/272 (31.6%) of unsafe-drinkers had AFLD [males-85; mean-age 50.2 (SD-8.6) years]. Males [p<0.001], increased waist circumference (WC) [p=0.001], BMI>23kg/m2 [p<0.001], raised triglycerides (TG) [p<0.001], low education level (LEL-not completed secondary-education) [p<0.01] and low monthly household-income (23kg/m2 [p<0.001], raised TG [p<0.001] and LEL [p<0.05] independently predicted incident-AFLD. The genetic association study [133-cases (combined 2007-2014), 97-controls] showed no association with AFLD at PNPLA3 (rs738409). CONCLUSION: The prevalence of AFLD was 2.9% in 2007 and annual incidence among heavy drinkers, after 7-year follow-up was 5.7%. Incident-AFLD was associated with males, obesity, raised TG and LEL.Item Incidence, prevalence and demographic and life style risk factors for obesity among urban, adult Sri Lankans: a community cohort follow-up study(Sri Lanka Medical Association, 2017) Niriella, M.A.; de Silva, S.T.; Kasturiratne, A.; Kottachchi, D.; Ranasinghe, R.M.A.G.; Dassanayake, A.S.; de Silva, A.P.; Pathmeswaran, A.; Wickremasinghe, A.R.; Kato, N.; de Silva, H.J.INTRODUCTION & OBJECTIVES: Obesity is a global problem. Data from the South Asian region is limited. METHODS: In a cohort follow-up study we investigated obesity among urban, adult, Sri Lankans (35-64y; selected by age-stratified random sampling from Ragama-MOH area; initial screening 2007; re-evaluation 2014). On both occasions structured interview, anthropometry, liver ultrasound, biochemical and serological tests were performed. Total body fat (TBF) and visceral fat percentage (VFP) were assessed by impedance in 2014. General-obesity (GO) was BMI>25kg/m2. Central-obesity (CO) was waist circumference (WC)>90cm males and WC>80cm females. Multinomial logistic regression was fitted to assess associations. RESULTS: In 2007 (n=2967), 614 (20.7%) were overweight [51.9%-women], 1161(39.1%) had GO [65.9%-women] and 1584(53.4%) had CO [71%-women]. Females (p<0.001), raised-TG (p<0.001), low-HDL (p<0.001), diabetes (p<0.001), hypertension (p<0.001), NAFLD (p<0.001), and low household income (p<0.001) were significantly associated with prevalent GO and CO respectively. Additionally, increased-age (p=0.05), low-educational level (p<0.001) and unhealthy eating (p<0.001) were associated with prevalent CO. Inadequate physical activity was not associated with either. 2137 (72%) attended follow-up in 2014. Of those who were initially non-obese who attended follow-up, 189/1270 (14.9%) [64% women] had developed GO (annual-incidence 2.13%) and 206/947 (21.9%) [56.3% women] had developed CO (annual incidence 3.12%) after 7 years. TBF and VFP significantly correlated with incident GO and CO (p<0.001). Female gender (OR-1.78, p<0.001; 2.81, p<0.001) and NAFLD (OR-2.93, p<0.001; OR-2.27, p<0.001) independently predicted incident GO and CO respectively. CONCLUSION: The prevalence and incidence of GO and CO were high in this cohort. Both incident GO and CO were strongly associated with female gender and NAFLD.Item Lean non-alcoholic fatty liver disease (Lean-NAFLD): characteristics and risk factors from a community cohort follow up study(Sri Lanka Medical Association, 2016) Niriella, M.A.; de Silva, S.T.; Kasturiratne, A.; Perera, K.R.; Subasinghe, S.K.C.E.; Kodisinghe, S.K.; Piyaratna, T.A.C.L.; Vithiya, K.; Dassanayake, A.S.; de Silva, A.P.; Pathmeswaran, A.; Wickremasinghe, A.R.; Kato, N.; de Silva, H.J.INTRODUCTION AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is usually associated with obesity. However, some NAFLD patients are lean. We assessed the characteristics and risk factors for lean-NAFLD. METHOD: In a community cohort follow up study (initial screening-2007, re-evaluation-2014), NAFLD was established on USS criteria and exclusion of alcohol overuse and secondary causes. Lean (BMI <23 kg/m2) and non-lean (BMI ≥23 kg/m2) NAFLD were compared. The two groups were compared for differences in gender, diabetes, hypertension, hypertriglyceridemia, low-HDL, weight and waist circumference (WC) at baseline. They were also compared for differences in development of incident diabetes, hypertension, hypertriglyceridemia, low-HDL, and change in weight and WC. RESULTS: 678 (69.6%) individuals with NAFLD detected in 2007 presented for follow up in 2014. 78(11.5%) [males-32(41%); mean-age 53.7(SD-7.1) years] were lean and 600(88.5%) [males-191(31.8%); mean-age 52.3(SD-7.5) years] were non-lean. Hypertension (p=0.007) and a smaller WC (<90cm for males, <80cm for females) (p<0.001) were associated with lean-NAFLD. After 7 years, change in BMI was less (p=0.022) among lean-NAFLD. There were no differences in change in WC or incident metabolic co-morbidities. Of those who did not have NAFLD in 2007, 746 developed incident NAFLD in 2014; lean-NAFLD 193/746 (25.9%) [males-100(51.8%); mean age 59.6(SD-7.5)], non-lean-NAFLD 553/746 (74.1%) [males-201(36.3%); mean age 58.2(SD-7.7)]. On logistic regression analysis, presence of diabetes (p=0.002, OR 2.1) and raised WC (p=0.003, OR 1.7) were associated with incident lean-NAFLD. CONCLUSIONS: Among individuals with NAFLD, lean-NAFLD is associated with hypertension and smaller WC. In the community, diabetes and bigger WC predict incident lean-NAFLD.Item Incidence and risk factors for Non-Alcoholic Fatty Liver Disease in an urban, adult Sri Lankan population – a community cohort follow-up study(Sage Publishing, 2015) Niriella, M.; Kasturiratne, A.; de Silva, S.; Perera, R.; Subasinghe, C.; Kodisinghe, K.; Priyantha, C.; Rishikeshavan, V.; Dassanayake, A.; de Silva, A.; Pathmeswaran, A.; Kato, N.; de Silva, H.J.INTRODUCTION: We previously reported a community prevalence of 33% for NAFLD in an urban, adult Sri Lankan population. We also found a significant association between patatin-like phospholipase domain containing 3 (PNPLA3) gene rs738409 polymorphism, and susceptibility to NAFLD in the same population, after testing 10 selected single nucleotide polymorphisms (SNPs) in a case control study. AIMS & METHODS: The aim of this study was to assess the incidence and risk factors for NAFLD in this population after seven years of follow-up. The study population consisted of 42-71-year-old adults, originally selected by age stratified random sampling from electoral lists from Ragama, Sri Lanka. The target population was screened initially in 2007 and subsequently invited back for re-evaluation in 2014. On both occasions they were assessed using a structured interview, clinical and anthropometric measurements, liver ultrasound, and biochemical and serological tests. NAFLD was diagnosed on established ultrasound criteria for fatty liver (two out of three criteria: increased echogenecity of the liver compared to kidney and spleen, obliteration of the vascular architecture of the liver and deep attenuation of the ultrasonic signal), safe alcohol consumption (Asian standards: 514 units/week for men, 57 units/week for females) and absence of hepatitis B and C markers. Non-NAFLD controls were defined as subjects who did not have any of the ultrasound criteria for NAFLD. We also performed an updated case-control study to investigate associations of selected genetic variants with incident NAFLD [SNPs: PNPLA3 (rs738409), LYPLAL1 (rs12137855), GCKR (rs780094), PPP1R3B (rs4240624) and NCAN (rs2228603), APOC3 (rs2854117 and rs2854116), ADIPOR2 (rs767870) and STAT3 (rs6503695 and rs9891119)]. RESULTS: Of the 2985 original study participants, 2155 (72.2%) (1244 women and 911 men; mean age 59.2 years [SD, 7.7]) participated in the follow-up assessment. 1322 [mean age 58.9 years (SD, 7.6), 483 (53.0%) men and 839 (67.4%) women] had NAFLD. Out of 795 [466 (58.6%) women] participants who did not have NAFLD in the original study, 365 [226 (61.9%) women, mean age 58.6 years (SD, 7.9)] had developed NAFLD after 7 years, giving an annual incidence rate 6.6%. On multivariate analysis, increased waist circumference [OR 1.96(1.30 – 2.97), p=0.001], BMI4 23 kg/m2 [OR 2.93(1.99 – 4.30), p50.001] and raised plasma triglycerides (TG) [OR 1.49(1.03 – 2.13), p=0.03] were independently predictive of incident NAFLD in this cohort, while raised BP and reduced HDL, were not. In the updated association study involving 1310 cases and 427 controls, we found borderline association with NAFLD at two of the 10 candidate loci: rs4240624 at PPP1R3B and rs738409 at PNPLA3 (one-tailed P=0.044 and 0.033, respectively). CONCLUSION: In this community cohort follow-up study in an urban, adult population in Sri Lanka, the annual incidence of NAFLD was 6.6%. Incident NAFLD was associated with features of the metabolic syndrome, and showed tendency of association at PNPLA3 and PPP1R3B gene polymorphisms. Disclosure of Interest: None declaredItem Genetic variants of NAFLD in an urban Sri Lankan community(Wiley Blackwell Scientific Publications, 2013) Niriella, M.A.; Kasturiratne, A.; Akiyama, K.; Takeuchi, F.; Isono, M.; Dassanayake, A.S.; de Silva, A.P.; Wickremasinghe, A.R.; Kato, N.; de Silva, H.J.OBJECTIVE: Recently, genome-wide association studies (GWAS) have successfully identified loci associated with susceptibility to non-alcoholic fatty liver disease (NAFLD) in populations of European descent. No large-scale genetic studies have been performed thus far in South Asian populations. Therefore, as part of a community-based cohort study in an urban adult population of Sri Lankans, we investigated associations of genetic variants with NAFLD, diagnosed on established ultrasound criteria, and its related phenotypes. METHODS: We selected 10 single nucleotide polymorphisms (SNPs), all previously reported to be associated with NAFLD in populations of European and/or South Asian ancestry, for a case-control replication study. They included loci derived from GWAS [PNPLA3 (rs738409), LYPLAL1 (rs12137855), GCKR (rs780094), PPP1R3B (rs4240624) and NCAN (rs2228603)] plus those from candidate gene studies [APOC3 (rs2854117 and rs2854116), ADIPOR2 (rs767870) and STAT3 (rs6503695 and rs9891119)]. Genotype data of 2988 participants were used for the analysis. RESULTS: A significant NAFLD association was observed for PNPLA3 (rs738409) [OR = 1.25, 95% CI 1.08–1.44, P = 0.003)]; rs738409 was also associated with a trend towards lower serum triglycerides APOC3 variants were significantly (P = 7.3–7.5 × 10–8) associated with higher triglycerides, but not with NAFLD (OR = 0.86). Apart from SNP–lipid associations previously reported at the GCKR, PPP1R3B and NCAN loci, there were no other prominent associations. CONCLUSION: Our data confirm that the PNPLA3 gene variant is significantly associated with NAFLD in the general Sri Lankan population but could not replicate previously reported disease associations at other loci, reinforcing the importance of further large-scale study on genetic variants in diverse populations to better understand the pathophysiology of NAFLD.