Acquisition and extinction across multiple virtual reality contexts: implications for specific phobias and current treatment methods

Victor Wong studied human acquisition learning over multiple contexts using virtual reality. He found that learning an association over multiple contexts can impact subsequent extinction training. This suggests that fears acquired over multiple contexts may be more difficult to treat using exposure-based therapies and will need to be augmented for effectiveness

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer

Developing a Diagnostic Multivariable Prediction Model for Urinary Tract Cancer in Patients Referred with Haematuria: Results from the IDENTIFY Collaborative Study

377siBackground: Patient factors associated with urinary tract cancer can be used to risk stratify patients referred with haematuria, prioritising those with a higher risk of cancer for prompt investigation. Objective: To develop a prediction model for urinary tract cancer in patients referred with haematuria. Design, setting, and participants: A prospective observational study was conducted in 10 282 patients from 110 hospitals across 26 countries, aged ≥16 yr and referred to secondary care with haematuria. Patients with a known or previous urological malignancy were excluded. Outcome measurements and statistical analysis: The primary outcomes were the presence or absence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC], and renal cancer). Mixed-effect multivariable logistic regression was performed with site and country as random effects and clinically important patient-level candidate predictors, chosen a priori, as fixed effects. Predictors were selected primarily using clinical reasoning, in addition to backward stepwise selection. Calibration and discrimination were calculated, and bootstrap validation was performed to calculate optimism. Results and limitations: The unadjusted prevalence was 17.2% (n = 1763) for bladder cancer, 1.20% (n = 123) for UTUC, and 1.00% (n = 103) for renal cancer. The final model included predictors of increased risk (visible haematuria, age, smoking history, male sex, and family history) and reduced risk (previous haematuria investigations, urinary tract infection, dysuria/suprapubic pain, anticoagulation, catheter use, and previous pelvic radiotherapy). The area under the receiver operating characteristic curve of the final model was 0.86 (95% confidence interval 0.85-0.87). The model is limited to patients without previous urological malignancy. Conclusions: This cancer prediction model is the first to consider established and novel urinary tract cancer diagnostic markers. It can be used in secondary care for risk stratifying patients and aid the clinician's decision-making process in prioritising patients for investigation. Patient summary: We have developed a tool that uses a person's characteristics to determine the risk of cancer if that person develops blood in the urine (haematuria). This can be used to help prioritise patients for further investigation.noneopenKhadhouri, Sinan; Gallagher, Kevin M.; MacKenzie, Kenneth R.; Shah, Taimur T.; Gao, Chuanyu; Moore, Sacha; Zimmermann, Eleanor F.; Edison, Eric; Jefferies, Matthew; Nambiar, Arjun; Anbarasan, Thineskrishna; Mannas, Miles P.; Lee, Taeweon; Marra, Giancarlo; Gómez Rivas, Juan; Marcq, Gautier; Assmus, Mark A.; Uçar, Taha; Claps, Francesco; Boltri, Matteo; La Montagna, Giuseppe; Burnhope, Tara; Nkwam, Nkwam; Austin, Tomas; Boxall, Nicholas E.; Downey, Alison P.; Sukhu, Troy A.; Antón-Juanilla, Marta; Rai, Sonpreet; Chin, Yew-Fung; Moore, Madeline; Drake, Tamsin; Green, James S.A.; Goulao, Beatriz; MacLennan, Graeme; Nielsen, Matthew; McGrath, John S.; Kasivisvanathan, Veeru; Chaudry, Aasem; Sharma, Abhishek; Bennett, Adam; Ahmad, Adnan; Abroaf, Ahmed; Suliman, Ahmed Musa; Lloyd, Aimee; McKay, Alastair; Wong, Albert; Silva, Alberto; Schneider, Alexandre; MacKay, Alison; Knight, Allen; Grigorakis, Alkiviadis; Bdesha, Amar; Nagle, Amy; Cebola, Ana; Dhanasekaran, Ananda Kumar; Kondža, Andraž; Barcelos, André; Galosi, Andrea Benedetto; Ebur, Andrea; Minervini, Andrea; Russell, Andrew; Webb, Andrew; de Jalón, Ángel García; Desai, Ankit; Czech, Anna Katarzyna; Mainwaring, Anna; Adimonye, Anthony; Das, Arighno; Figueiredo, Arnaldo; Villers, Arnauld; Leminski, Artur; Chippagiri, Arvinda; Lal, Asim Ahmed; Yıldırım, Asıf; Voulgaris, Athanasios Marios; Uzan, Audrey; Oo, Aye Moh Moh; Younis, Ayman; Zelhof, Bachar; Mukhtar, Bashir; Ayres, Ben; Challacombe, Ben; Sherwood, Benedict; Ristau, Benjamin; Lai, Billy; Nellensteijn, Brechtje; Schreiter, Brielle; Trombetta, Carlo; Dowling, Catherine; Hobbs, Catherine; Benitez, Cayo Augusto Estigarribia; Lebacle, Cédric; Ho, Cherrie Wing Yin; Ng, Chi-Fai; Mount, Chloe; Lam, Chon Meng; Blick, Chris; Brown, Christian; Gallegos, Christopher; Higgs, Claire; Browne, Clíodhna; McCann, Conor; Plaza Alonso, Cristina; Beder, Daniel; Cohen, Daniel; Gordon, Daniel; Wilby, Daniel; Gordon, Danny; Hrouda, David; Lau, David Hua Wu; Karsza, Dávid; Mak, David; Martin-Way, David; Suthaharan, Denula; Patel, Dhruv; Carrion, Diego M; Nyanhongo, Donald; Bass, Edward; Mains, Edward; Chau, Edwin; Canelon Castillo, Elba; Day, Elizabeth; Desouky, Elsayed; Gaines, Emily; Papworth, Emma; Yuruk, Emrah; Kilic, Enes; Dinneen, Eoin; Palagonia, Erika; Xylinas, Evanguelos; Khawaja, Faizan; Cimarra, Fernando; Bardet, Florian; Kum, Francesca; Peters, Francesca; Kovács, Gábor; Tanasescu, Geroge; Hellawell, Giles; Tasso, Giovanni; Lam, Gitte; La Montagna, Giuseppe; Pizzuto, Giuseppe; Lenart, Gordan; MacLennan, Graeme; Özgür, Günal; Bi, Hai; Lyons, Hannah; Warren, Hannah; Ahmed, Hashim; Simpson, Helen; Burden, Helena; Gresty, Helena; Rios Pita, Hernado; Clarke, Holly; Serag, Hosam; Kynaston, Howard; Crawford-Smith, Hugh; Mostafid, Hugh; Otaola-Arca, Hugo; Koo, Hui Fen; Ibrahim, Ibrahim; Ouzaid, Idir; Puche-Sanz, Ignacio; Tomašković, Igor; Tinay, Ilker; Sahibzada, Iqbal; Thangasamy, Isaac; Cadena, Iván Revelo; Irani, Jacques; Udzik, Jakub; Brittain, James; Catto, James; Green, James; Tweedle, James; Hernando, Jamie Borrego; Leask, Jamie; Kalsi, Jas; Frankel, Jason; Toniolo, Jason; Raman, Jay D.; Courcier, Jean; Kumaradeevan, Jeevan; Clark, Jennifer; Jones, Jennifer; Teoh, Jeremy Yuen-Chun; Iacovou, John; Kelly, John; Selph, John P.; Aning, Jonathan; Deeks, Jon; Cobley, Jonathan; Olivier, Jonathan; Maw, Jonny; Herranz-Yagüe, José Antonio; Nolazco, Jose Ignacio; Cózar-Olmo, Jose Manuel; Bagley, Joseph; Jelski, Joseph; Norris, Joseph; Testa, Joseph; Meeks, Joshua; Hernandez, Juan; Vásquez, Juan Luis; Randhawa, Karen; Dhera, Karishma; Gronostaj, Katarzyna; Houlton, Kathleen; Lehman, Kathleen; Gillams, Kathryn; Adasonla, Kelvin; Brown, Kevin; Murtagh, Kevin; Mistry, Kiki; Davenport, Kim; Kitamura, Kosuke; Derbyshire, Laura; Clarke, Laurence; Morton, Lawrie; Martinez, Levin; Goldsmith, Louise; Paramore, Louise; Cormier, Luc; Dell'Atti, Lucio; Simmons, Lucy; Martinez-Piñeiro, Luis; Rico, Luis; Chan, Luke; Forster, Luke; Ma, Lulin; Moore, Madeline; Gallego, Maria Camacho; Freire, Maria José; Emberton, Mark; Feneley, Mark; Antón-Juanilla, Marta; Rivero, Marta Viridiana Muñoz; Pirša, Matea; Tallè, Matteo; Crockett, Matthew; Liew, Matthew; Trail, Matthew; Peters, Max; Cooper, Meghan; Kulkarni, Meghana; Ager, Michael; He, Ming; Li, Mo; Omran Breish, Mohamed; Tarin, Mohamed; Aldiwani, Mohammed; Matanhelia, Mudit; Pasha, Muhammad; Akalın, Mustafa Kaan; Abdullah, Nasreen; Hale, Nathan; Gadiyar, Neha; Kocher, Neil; Bullock, Nicholas; Campain, Nicholas; Pavan, Nicola; Al-Ibraheem, Nihad; Bhatt, Nikita; Bedi, Nishant; Shrotri, Nitin; Lobo, Niyati; Balderas, Olga; Kouli, Omar; Capoun, Otakar; Oteo Manjavacas, Pablo; Gontero, Paolo; Mariappan, Paramananthan; Marchiñena, Patricio Garcia; Erotocritou, Paul; Sweeney, Paul; Planelles, Paula; Acher, Peter; Black, Peter C.; Osei-Bonsu, Peter K; Østergren, Peter; Smith, Peter; Willemse, Peter-Paul Michiel; Chlosta, Piotr L.; Ul Ain, Qurrat; Barratt, Rachel; Esler, Rachel; Khalid, Raihan; Hsu, Ray; Stamirowski, Remigiusz; Mangat, Reshma; Cruz, Ricardo; Ellis, Ricky; Adams, Robert; Hessell, Robert; Oomen, Robert J.A.; McConkey, Robert; Ritchie, Robert; Jarimba, Roberto; Chahal, Rohit; Andres, Rosado Mario; Hawkins, Rosalyn; David, Rotimi; Manecksha, Rustom P.; Agrawal, Sachin; Hamid, Syed Sami; Deem, Samuel; Goonewardene, Sanchia; Swami, Satchi Kuchibhotla; Hori, Satoshi; Khan, Shahid; Mohammud Inder, Shakeel; Sangaralingam, Shanthi; Marathe, Shekhar; Raveenthiran, Sheliyan; Horie, Shigeo; Sengupta, Shomik; Parson, Sian; Parker, Sidney; Hawlina, Simon; Williams, Simon; Mazzoli, Simone; Grzegorz Kata, Slawomir; Pinheiro Lopes, Sofia; Ramos, Sónia; Rai, Sonpreet; Rintoul-Hoad, Sophie; O'Meara, Sorcha; Morris, Steve; Turner, Stacey; Venturini, Stefano; Almpanis, Stephanos; Joniau, Steven; Jain, Sunjay; Mallett, Susan; Nikles, Sven; Shahzad, null; Yan, Sylvia; Lee, Taeweon; Uçar, Taha; Drake, Tamsin; Toma, Tarq; Cabañuz Plo, Teresa; Bonnin, Thierry; Muilwijk, Tim; Wollin, Tim; Chu, Timothy Shun Man; Appanna, Timson; Brophy, Tom; Ellul, Tom; Austin, Tomas; Smrkolj, Tomaž; Rowe, Tracey; Sukhu, Troy; Patel, Trushar; Garg, Tullika; Çaşkurlu, Turhan; Bele, Uros; Haroon, Usman; Crespo-Atín, Víctor; Parejo Cortes, Victor; Capapé Poves, Victoria; Gnanapragasam, Vincent; Gauhar, Vineet; During, Vinnie; Kumar, Vivek; Fiala, Vojtech; Mahmalji, Wasim; Lam, Wayne; Fung Chin, Yew; Filtekin, Yigit; Chyn Phan, Yih; Ibrahim, Youssed; Glaser, Zachary A; Abiddin, Zainal Adwin; Qin, Zijian; Zotter, Zsuzsanna; Zainuddin, ZulkifliKhadhouri, Sinan; Gallagher, Kevin M.; Mackenzie, Kenneth R.; Shah, Taimur T.; Gao, Chuanyu; Moore, Sacha; Zimmermann, Eleanor F.; Edison, Eric; Jefferies, Matthew; Nambiar, Arjun; Anbarasan, Thineskrishna; Mannas, Miles P.; Lee, Taeweon; Marra, Giancarlo; Gómez Rivas, Juan; Marcq, Gautier; Assmus, Mark A.; Uçar, Taha; Claps, Francesco; Boltri, Matteo; La Montagna, Giuseppe; Burnhope, Tara; Nkwam, Nkwam; Austin, Tomas; Boxall, Nicholas E.; Downey, Alison P.; Sukhu, Troy A.; Antón-Juanilla, Marta; Rai, Sonpreet; Chin, Yew-Fung; Moore, Madeline; Drake, Tamsin; Green, James S. A.; Goulao, Beatriz; Maclennan, Graeme; Nielsen, Matthew; Mcgrath, John S.; Kasivisvanathan, Veeru; Chaudry, Aasem; Sharma, Abhishek; Bennett, Adam; Ahmad, Adnan; Abroaf, Ahmed; Suliman, Ahmed Musa; Lloyd, Aimee; Mckay, Alastair; Wong, Albert; Silva, Alberto; Schneider, Alexandre; Mackay, Alison; Knight, Allen; Grigorakis, Alkiviadis; Bdesha, Amar; Nagle, Amy; Cebola, Ana; Dhanasekaran, Ananda Kumar; Kondža, Andraž; Barcelos, André; Galosi, Andrea Benedetto; Ebur, Andrea; Minervini, Andrea; Russell, Andrew; Webb, Andrew; de Jalón, Ángel García; Desai, Ankit; Czech, Anna Katarzyna; Mainwaring, Anna; Adimonye, Anthony; Das, Arighno; Figueiredo, Arnaldo; Villers, Arnauld; Leminski, Artur; Chippagiri, Arvinda; Lal, Asim Ahmed; Yıldırım, Asıf; Voulgaris, Athanasios Marios; Uzan, Audrey; Oo, Aye Moh Moh; Younis, Ayman; Zelhof, Bachar; Mukhtar, Bashir; Ayres, Ben; Challacombe, Ben; Sherwood, Benedict; Ristau, Benjamin; Lai, Billy; Nellensteijn, Brechtje; Schreiter, Brielle; Trombetta, Carlo; Dowling, Catherine; Hobbs, Catherine; Benitez, Cayo Augusto Estigarribia; Lebacle, Cédric; Ho, Cherrie Wing Yin; Ng, Chi-Fai; Mount, Chloe; Lam, Chon Meng; Blick, Chris; Brown, Christian; Gallegos, Christopher; Higgs, Claire; Browne, Clíodhna; Mccann, Conor; Plaza Alonso, Cristina; Beder, Daniel; Cohen, Daniel; Gordon, Daniel; Wilby, Daniel; Gordon, Danny; Hrouda, David; Lau, David Hua Wu; Karsza, Dávid; Mak, David; Martin-Way, David; Suthaharan, Denula; Patel, Dhruv; Carrion, Diego M; Nyanhongo, Donald; Bass, Edward; Mains, Edward; Chau, Edwin; Canelon Castillo, Elba; Day, Elizabeth; Desouky, Elsayed; Gaines, Emily; Papworth, Emma; Yuruk, Emrah; Kilic, Enes; Dinneen, Eoin; Palagonia, Erika; Xylinas, Evanguelos; Khawaja, Faizan; Cimarra, Fernando; Bardet, Florian; Kum, Francesca; Peters, Francesca; Kovács, Gábor; Tanasescu, Geroge; Hellawell, Giles; Tasso, Giovanni; Lam, Gitte; La Montagna, Giuseppe; Pizzuto, Giuseppe; Lenart, Gordan; Maclennan, Graeme; Özgür, Günal; Bi, Hai; Lyons, Hannah; Warren, Hannah; Ahmed, Hashim; Simpson, Helen; Burden, Helena; Gresty, Helena; Rios Pita, Hernado; Clarke, Holly; Serag, Hosam; Kynaston, Howard; Crawford-Smith, Hugh; Mostafid, Hugh; Otaola-Arca, Hugo; Koo, Hui Fen; Ibrahim, Ibrahim; Ouzaid, Idir; Puche-Sanz, Ignacio; Tomašković, Igor; Tinay, Ilker; Sahibzada, Iqbal; Thangasamy, Isaac; Cadena, Iván Revelo; Irani, Jacques; Udzik, Jakub; Brittain, James; Catto, James; Green, James; Tweedle, James; Hernando, Jamie Borrego; Leask, Jamie; Kalsi, Jas; Frankel, Jason; Toniolo, Jason; Raman, Jay D.; Courcier, Jean; Kumaradeevan, Jeevan; Clark, Jennifer; Jones, Jennifer; Teoh, Jeremy Yuen-Chun; Iacovou, John; Kelly, John; Selph, John P.; Aning, Jonathan; Deeks, Jon; Cobley, Jonathan; Olivier, Jonathan; Maw, Jonny; Herranz-Yagüe, José Antonio; Nolazco, Jose Ignacio; Cózar-Olmo, Jose Manuel; Bagley, Joseph; Jelski, Joseph; Norris, Joseph; Testa, Joseph; Meeks, Joshua; Hernandez, Juan; Vásquez, Juan Luis; Randhawa, Karen; Dhera, Karishma; Gronostaj, Katarzyna; Houlton, Kathleen; Lehman, Kathleen; Gillams, Kathryn; Adasonla, Kelvin; Brown, Kevin; Murtagh, Kevin; Mistry, Kiki; Davenport, Kim; Kitamura, Kosuke; Derbyshire, Laura; Clarke, Laurence; Morton, Lawrie; Martinez, Levin; Goldsmith, Louise; Paramore, Louise; Cormier, Luc; Dell'Atti, Lucio; Simmons, Lucy; Martinez-Piñeiro, Luis; Rico, Luis; Chan, Luke; Forster, Luke; Ma, Lulin; Moore, Madeline; Gallego, Maria Camacho; Freire, Maria José; Emberton, Mark; Feneley, Mark; Antón-Juanilla, Marta; Rivero, Marta Viridiana Muñoz; Pirša, Matea; Tallè, Matteo; Crockett, Matthew; Liew, Matthew; Trail, Matthew; Peters, Max; Cooper, Meghan; Kulkarni, Meghana; Ager, Michael; He, Ming; Li, Mo; Omran Breish, Mohamed; Tarin, Mohamed; Aldiwani, Mohammed; Matanhelia, Mudit; Pasha, Muhammad; Akalın, Mustafa Kaan; Abdullah, Nasreen; Hale, Nathan; Gadiyar, Neha; Kocher, Neil; Bullock, Nicholas; Campain, Nicholas; Pavan, Nicola; Al-Ibraheem, Nihad; Bhatt, Nikita; Bedi, Nishant; Shrotri, Nitin; Lobo, Niyati; Balderas, Olga; Kouli, Omar; Capoun, Otakar; Oteo Manjavacas, Pablo; Gontero, Paolo; Mariappan, Paramananthan; Marchiñena, Patricio Garcia; Erotocritou, Paul; Sweeney, Paul; Planelles, Paula; Acher, Peter; Black, Peter C.; Osei-Bonsu, Peter K; Østergren, Peter; Smith, Peter; Willemse, Peter-Paul Michiel; Chlosta, Piotr L.; Ul Ain, Qurrat; Barratt, Rachel; Esler, Rachel; Khalid, Raihan; Hsu, Ray; Stamirowski, Remigiusz; Mangat, Reshma; Cruz, Ricardo; Ellis, Ricky; Adams, Robert; Hessell, Robert; Oomen, Robert J. A.; Mcconkey, Robert; Ritchie, Robert; Jarimba, Roberto; Chahal, Rohit; Andres, Rosado Mario; Hawkins, Rosalyn; David, Rotimi; Manecksha, Rustom P.; Agrawal, Sachin; Hamid, Syed Sami; Deem, Samuel; Goonewardene, Sanchia; Swami, Satchi Kuchibhotla; Hori, Satoshi; Khan, Shahid; Mohammud Inder, Shakeel; Sangaralingam, Shanthi; Marathe, Shekhar; Raveenthiran, Sheliyan; Horie, Shigeo; Sengupta, Shomik; Parson, Sian; Parker, Sidney; Hawlina, Simon; Williams, Simon; Mazzoli, Simone; Grzegorz Kata, Slawomir; Pinheiro Lopes, Sofia; Ramos, Sónia; Rai, Sonpreet; Rintoul-Hoad, Sophie; O'Meara, Sorcha; Morris, Steve; Turner, Stacey; Venturini, Stefano; Almpanis, Stephanos; Joniau, Steven; Jain, Sunjay; Mallett, Susan; Nikles, Sven; Shahzad, Null; Yan, Sylvia; Lee, Taeweon; Uçar, Taha; Drake, Tamsin; Toma, Tarq; Cabañuz Plo, Teresa; Bonnin, Thierry; Muilwijk, Tim; Wollin, Tim; Chu, Timothy Shun Man; Appanna, Timson; Brophy, Tom; Ellul, Tom; Austin, Tomas; Smrkolj, Tomaž; Rowe, Tracey; Sukhu, Troy; Patel, Trushar; Garg, Tullika; Çaşkurlu, Turhan; Bele, Uros; Haroon, Usman; Crespo-Atín, Víctor; Parejo Cortes, Victor; Capapé Poves, Victoria; Gnanapragasam, Vincent; Gauhar, Vineet; During, Vinnie; Kumar, Vivek; Fiala, Vojtech; Mahmalji, Wasim; Lam, Wayne; Fung Chin, Yew; Filtekin, Yigit; Chyn Phan, Yih; Ibrahim, Youssed; Glaser, Zachary A; Abiddin, Zainal Adwin; Qin, Zijian; Zotter, Zsuzsanna; Zainuddin, Zulkifl

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P &lt; 5 × 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with &gt;50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care