@article {6811, title = {Association of Cardiometabolic Multimorbidity With Mortality.}, journal = {JAMA}, volume = {314}, year = {2015}, month = {2015 Jul 7}, pages = {52-60}, abstract = {

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing.

OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.

DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates.

EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).

MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy.

RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95\% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95\% CI, 2.0-2.2) in those with stroke, 2.0 (95\% CI, 1.9-2.2) in those with MI, 3.7 (95\% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95\% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95\% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95\% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.

CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

}, keywords = {Adult, Aged, Comorbidity, Diabetes Mellitus, Female, Humans, Life Expectancy, Male, Middle Aged, Mortality, Myocardial Infarction, Risk Factors, Stroke}, issn = {1538-3598}, doi = {10.1001/jama.2015.7008}, author = {Di Angelantonio, Emanuele and Kaptoge, Stephen and Wormser, David and Willeit, Peter and Butterworth, Adam S and Bansal, Narinder and O{\textquoteright}Keeffe, Linda M and Gao, Pei and Wood, Angela M and Burgess, Stephen and Freitag, Daniel F and Pennells, Lisa and Peters, Sanne A and Hart, Carole L and H{\r a}heim, Lise Lund and Gillum, Richard F and Nordestgaard, B{\o}rge G and Psaty, Bruce M and Yeap, Bu B and Knuiman, Matthew W and Nietert, Paul J and Kauhanen, Jussi and Salonen, Jukka T and Kuller, Lewis H and Simons, Leon A and van der Schouw, Yvonne T and Barrett-Connor, Elizabeth and Selmer, Randi and Crespo, Carlos J and Rodriguez, Beatriz and Verschuren, W M Monique and Salomaa, Veikko and Sv{\"a}rdsudd, Kurt and van der Harst, Pim and Bj{\"o}rkelund, Cecilia and Wilhelmsen, Lars and Wallace, Robert B and Brenner, Hermann and Amouyel, Philippe and Barr, Elizabeth L M and Iso, Hiroyasu and Onat, Altan and Trevisan, Maurizio and D{\textquoteright}Agostino, Ralph B and Cooper, Cyrus and Kavousi, Maryam and Welin, Lennart and Roussel, Ronan and Hu, Frank B and Sato, Shinichi and Davidson, Karina W and Howard, Barbara V and Leening, Maarten J G and Leening, Maarten and Rosengren, Annika and D{\"o}rr, Marcus and Deeg, Dorly J H and Kiechl, Stefan and Stehouwer, Coen D A and Nissinen, Aulikki and Giampaoli, Simona and Donfrancesco, Chiara and Kromhout, Daan and Price, Jackie F and Peters, Annette and Meade, Tom W and Casiglia, Edoardo and Lawlor, Debbie A and Gallacher, John and Nagel, Dorothea and Franco, Oscar H and Assmann, Gerd and Dagenais, Gilles R and Jukema, J Wouter and Sundstr{\"o}m, Johan and Woodward, Mark and Brunner, Eric J and Khaw, Kay-Tee and Wareham, Nicholas J and Whitsel, Eric A and Nj{\o}lstad, Inger and Hedblad, Bo and Wassertheil-Smoller, Sylvia and Engstr{\"o}m, Gunnar and Rosamond, Wayne D and Selvin, Elizabeth and Sattar, Naveed and Thompson, Simon G and Danesh, John} } @article {7596, title = {Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis.}, journal = {PLoS Med}, volume = {14}, year = {2017}, month = {2017 Sep}, pages = {e1002383}, abstract = {

BACKGROUND: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

METHODS \& FINDINGS: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95\% CI 1.04-1.06, per HbA1c-raising allele, p = 3 {\texttimes} 10-29); whereas GS-E was not (OR = 1.00, 95\% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11\%) was associated with an absolute decrease in HbA1c of 0.81\%-units (95\% CI 0.66-0.96) per allele in hemizygous men, and 0.68\%-units (95\% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2\% (N = 0.65 million, 95\% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.

CONCLUSIONS: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

}, keywords = {Diabetes Mellitus, Type 2, Genetic Variation, Genome-Wide Association Study, Glycated Hemoglobin A, Humans, Phenotype, Risk}, issn = {1549-1676}, doi = {10.1371/journal.pmed.1002383}, author = {Wheeler, Eleanor and Leong, Aaron and Liu, Ching-Ti and Hivert, Marie-France and Strawbridge, Rona J and Podmore, Clara and Li, Man and Yao, Jie and Sim, Xueling and Hong, Jaeyoung and Chu, Audrey Y and Zhang, Weihua and Wang, Xu and Chen, Peng and Maruthur, Nisa M and Porneala, Bianca C and Sharp, Stephen J and Jia, Yucheng and Kabagambe, Edmond K and Chang, Li-Ching and Chen, Wei-Min and Elks, Cathy E and Evans, Daniel S and Fan, Qiao and Giulianini, Franco and Go, Min Jin and Hottenga, Jouke-Jan and Hu, Yao and Jackson, Anne U and Kanoni, Stavroula and Kim, Young Jin and Kleber, Marcus E and Ladenvall, Claes and Lecoeur, C{\'e}cile and Lim, Sing-Hui and Lu, Yingchang and Mahajan, Anubha and Marzi, Carola and Nalls, Mike A and Navarro, Pau and Nolte, Ilja M and Rose, Lynda M and Rybin, Denis V and Sanna, Serena and Shi, Yuan and Stram, Daniel O and Takeuchi, Fumihiko and Tan, Shu Pei and van der Most, Peter J and van Vliet-Ostaptchouk, Jana V and Wong, Andrew and Yengo, Loic and Zhao, Wanting and Goel, Anuj and Martinez Larrad, Maria Teresa and Radke, D{\"o}rte and Salo, Perttu and Tanaka, Toshiko and van Iperen, Erik P A and Abecasis, Goncalo and Afaq, Saima and Alizadeh, Behrooz Z and Bertoni, Alain G and Bonnefond, Am{\'e}lie and B{\"o}ttcher, Yvonne and Bottinger, Erwin P and Campbell, Harry and Carlson, Olga D and Chen, Chien-Hsiun and Cho, Yoon Shin and Garvey, W Timothy and Gieger, Christian and Goodarzi, Mark O and Grallert, Harald and Hamsten, Anders and Hartman, Catharina A and Herder, Christian and Hsiung, Chao Agnes and Huang, Jie and Igase, Michiya and Isono, Masato and Katsuya, Tomohiro and Khor, Chiea-Chuen and Kiess, Wieland and Kohara, Katsuhiko and Kovacs, Peter and Lee, Juyoung and Lee, Wen-Jane and Lehne, Benjamin and Li, Huaixing and Liu, Jianjun and Lobbens, Stephane and Luan, Jian{\textquoteright}an and Lyssenko, Valeriya and Meitinger, Thomas and Miki, Tetsuro and Miljkovic, Iva and Moon, Sanghoon and Mulas, Antonella and M{\"u}ller, Gabriele and M{\"u}ller-Nurasyid, Martina and Nagaraja, Ramaiah and Nauck, Matthias and Pankow, James S and Polasek, Ozren and Prokopenko, Inga and Ramos, Paula S and Rasmussen-Torvik, Laura and Rathmann, Wolfgang and Rich, Stephen S and Robertson, Neil R and Roden, Michael and Roussel, Ronan and Rudan, Igor and Scott, Robert A and Scott, William R and Sennblad, Bengt and Siscovick, David S and Strauch, Konstantin and Sun, Liang and Swertz, Morris and Tajuddin, Salman M and Taylor, Kent D and Teo, Yik-Ying and Tham, Yih Chung and T{\"o}njes, Anke and Wareham, Nicholas J and Willemsen, Gonneke and Wilsgaard, Tom and Hingorani, Aroon D and Egan, Josephine and Ferrucci, Luigi and Hovingh, G Kees and Jula, Antti and Kivimaki, Mika and Kumari, Meena and Nj{\o}lstad, Inger and Palmer, Colin N A and Serrano R{\'\i}os, Manuel and Stumvoll, Michael and Watkins, Hugh and Aung, Tin and Bl{\"u}her, Matthias and Boehnke, Michael and Boomsma, Dorret I and Bornstein, Stefan R and Chambers, John C and Chasman, Daniel I and Chen, Yii-Der Ida and Chen, Yduan-Tsong and Cheng, Ching-Yu and Cucca, Francesco and de Geus, Eco J C and Deloukas, Panos and Evans, Michele K and Fornage, Myriam and Friedlander, Yechiel and Froguel, Philippe and Groop, Leif and Gross, Myron D and Harris, Tamara B and Hayward, Caroline and Heng, Chew-Kiat and Ingelsson, Erik and Kato, Norihiro and Kim, Bong-Jo and Koh, Woon-Puay and Kooner, Jaspal S and K{\"o}rner, Antje and Kuh, Diana and Kuusisto, Johanna and Laakso, Markku and Lin, Xu and Liu, Yongmei and Loos, Ruth J F and Magnusson, Patrik K E and M{\"a}rz, Winfried and McCarthy, Mark I and Oldehinkel, Albertine J and Ong, Ken K and Pedersen, Nancy L and Pereira, Mark A and Peters, Annette and Ridker, Paul M and Sabanayagam, Charumathi and Sale, Michele and Saleheen, Danish and Saltevo, Juha and Schwarz, Peter Eh and Sheu, Wayne H H and Snieder, Harold and Spector, Timothy D and Tabara, Yasuharu and Tuomilehto, Jaakko and van Dam, Rob M and Wilson, James G and Wilson, James F and Wolffenbuttel, Bruce H R and Wong, Tien Yin and Wu, Jer-Yuarn and Yuan, Jian-Min and Zonderman, Alan B and Soranzo, Nicole and Guo, Xiuqing and Roberts, David J and Florez, Jose C and Sladek, Robert and Dupuis, Jos{\'e}e and Morris, Andrew P and Tai, E-Shyong and Selvin, Elizabeth and Rotter, Jerome I and Langenberg, Claudia and Barroso, In{\^e}s and Meigs, James B} } @article {7451, title = {REPEATED MEASUREMENTS OF BLOOD PRESSURE AND CHOLESTEROL IMPROVES CARDIOVASCULAR DISEASE RISK PREDICTION: AN INDIVIDUAL-PARTICIPANT-DATA META-ANALYSIS.}, journal = {Am J Epidemiol}, year = {2017}, month = {2017 May 26}, abstract = {

The added value of incorporating information from repeated measurements of blood pressure and cholesterol for cardiovascular disease (CVD) risk prediction has not been rigorously assessed. We used data from the Emerging Risk Factors Collaboration on 191,445 adults (38 cohorts from across 17 countries with data from 1962-2014) with~>~1 million measurements of systolic blood pressure, total cholesterol and high-density lipoprotein cholesterol; over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative means of repeated measurements and summary measures from longitudinal modelling of the repeated measurements were compared to models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analysed across studies. Compared to the single time point model, the cumulative means and the longitudinal models increased the C-index by 0.0040 (95\% CI: 0.0023, 0.0057) and 0.0023 (0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared to the single time point model, overall net reclassification improvements were 0.0369 (0.0303, 0.0436) for the cumulative means model and 0.0177 (0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

}, issn = {1476-6256}, doi = {10.1093/aje/kwx149}, author = {Paige, Ellie and Barrett, Jessica and Pennells, Lisa and Sweeting, Michael and Willeit, Peter and Di Angelantonio, Emanuele and Gudnason, Vilmundur and Nordestgaard, B{\o}rge G and Psaty, Bruce M and Goldbourt, Uri and Best, Lyle G and Assmann, Gerd and Salonen, Jukka T and Nietert, Paul J and Verschuren, Wm Monique and Brunner, Eric J and Kronmal, Richard A and Salomaa, Veikko and Bakker, Stephan Jl and Dagenais, Gilles R and Sato, Shinichi and Jansson, Jan-H{\r a}kan and Willeit, Johann and Onat, Altan and de la C{\'a}mara, Agustin G{\'o}mez and Roussel, Ronan and V{\"o}lzke, Henry and Dankner, Rachel and Tipping, Robert W and Meade, Tom W and Donfrancesco, Chiara and Kuller, Lewis H and Peters, Annette and Gallacher, John and Kromhout, Daan and Iso, Hiroyasu and Knuiman, Matthew and Casiglia, Edoardo and Kavousi, Maryam and Palmieri, Luigi and Sundstr{\"o}m, Johan and Davis, Barry R and Nj{\o}lstad, Inger and Couper, David and Danesh, John and Thompson, Simon G and Wood, Angela} } @article {7923, title = {Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.}, journal = {Eur Heart J}, year = {2018}, month = {2018 Nov 22}, abstract = {

Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after {\textquoteright}recalibration{\textquoteright}, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.

Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at {\textquoteright}high{\textquoteright} 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10\%, 52\%, and 41\%, respectively, whereas RRS under-predicted by 10\%. Original versions of algorithms classified 29-39\% of individuals aged >=40 years as high risk. By contrast, recalibration reduced this proportion to 22-24\% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms.

Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.

}, issn = {1522-9645}, doi = {10.1093/eurheartj/ehy653}, author = {Pennells, Lisa and Kaptoge, Stephen and Wood, Angela and Sweeting, Mike and Zhao, Xiaohui and White, Ian and Burgess, Stephen and Willeit, Peter and Bolton, Thomas and Moons, Karel G M and van der Schouw, Yvonne T and Selmer, Randi and Khaw, Kay-Tee and Gudnason, Vilmundur and Assmann, Gerd and Amouyel, Philippe and Salomaa, Veikko and Kivimaki, Mika and Nordestgaard, B{\o}rge G and Blaha, Michael J and Kuller, Lewis H and Brenner, Hermann and Gillum, Richard F and Meisinger, Christa and Ford, Ian and Knuiman, Matthew W and Rosengren, Annika and Lawlor, Debbie A and V{\"o}lzke, Henry and Cooper, Cyrus and Mar{\'\i}n Iba{\~n}ez, Alejandro and Casiglia, Edoardo and Kauhanen, Jussi and Cooper, Jackie A and Rodriguez, Beatriz and Sundstr{\"o}m, Johan and Barrett-Connor, Elizabeth and Dankner, Rachel and Nietert, Paul J and Davidson, Karina W and Wallace, Robert B and Blazer, Dan G and Bj{\"o}rkelund, Cecilia and Donfrancesco, Chiara and Krumholz, Harlan M and Nissinen, Aulikki and Davis, Barry R and Coady, Sean and Whincup, Peter H and J{\o}rgensen, Torben and Ducimetiere, Pierre and Trevisan, Maurizio and Engstr{\"o}m, Gunnar and Crespo, Carlos J and Meade, Tom W and Visser, Marjolein and Kromhout, Daan and Kiechl, Stefan and Daimon, Makoto and Price, Jackie F and G{\'o}mez de la C{\'a}mara, Agustin and Wouter Jukema, J and Lamarche, Beno{\^\i}t and Onat, Altan and Simons, Leon A and Kavousi, Maryam and Ben-Shlomo, Yoav and Gallacher, John and Dekker, Jacqueline M and Arima, Hisatomi and Shara, Nawar and Tipping, Robert W and Roussel, Ronan and Brunner, Eric J and Koenig, Wolfgang and Sakurai, Masaru and Pavlovic, Jelena and Gansevoort, Ron T and Nagel, Dorothea and Goldbourt, Uri and Barr, Elizabeth L M and Palmieri, Luigi and Nj{\o}lstad, Inger and Sato, Shinichi and Monique Verschuren, W M and Varghese, Cherian V and Graham, Ian and Onuma, Oyere and Greenland, Philip and Woodward, Mark and Ezzati, Majid and Psaty, Bruce M and Sattar, Naveed and Jackson, Rod and Ridker, Paul M and Cook, Nancy R and D{\textquoteright}Agostino, Ralph B and Thompson, Simon G and Danesh, John and Di Angelantonio, Emanuele} }