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1.  Targeted genetic testing for familial hypercholesterolaemia using next generation sequencing: a population-based study 
BMC Medical Genetics  2014;15:70.
Background
Familial hypercholesterolaemia (FH) is a common Mendelian condition which, untreated, results in premature coronary heart disease. An estimated 88% of FH cases are undiagnosed in the UK. We previously validated a method for FH mutation detection in a lipid clinic population using next generation sequencing (NGS), but this did not address the challenge of identifying index cases in primary care where most undiagnosed patients receive healthcare. Here, we evaluate the targeted use of NGS as a potential route to diagnosis of FH in a primary care population subset selected for hypercholesterolaemia.
Methods
We used microfluidics-based PCR amplification coupled with NGS and multiplex ligation-dependent probe amplification (MLPA) to detect mutations in LDLR, APOB and PCSK9 in three phenotypic groups within the Generation Scotland: Scottish Family Health Study including 193 individuals with high total cholesterol, 232 with moderately high total cholesterol despite cholesterol-lowering therapy, and 192 normocholesterolaemic controls.
Results
Pathogenic mutations were found in 2.1% of hypercholesterolaemic individuals, in 2.2% of subjects on cholesterol-lowering therapy and in 42% of their available first-degree relatives. In addition, variants of uncertain clinical significance (VUCS) were detected in 1.4% of the hypercholesterolaemic and cholesterol-lowering therapy groups. No pathogenic variants or VUCS were detected in controls.
Conclusions
We demonstrated that population-based genetic testing using these protocols is able to deliver definitive molecular diagnoses of FH in individuals with high cholesterol or on cholesterol-lowering therapy. The lower cost and labour associated with NGS-based testing may increase the attractiveness of a population-based approach to FH detection compared to genetic testing with conventional sequencing. This could provide one route to increasing the present low percentage of FH cases with a genetic diagnosis.
doi:10.1186/1471-2350-15-70
PMCID: PMC4083361  PMID: 24956927
Familial hypercholesterolaemia; Total cholesterol; LDLR; Molecular diagnostic testing; Next-generation sequencing; Primary care; Generation Scotland
2.  Pedigree and genotyping quality analyses of over 10,000 DNA samples from the Generation Scotland: Scottish Family Health Study 
BMC Medical Genetics  2013;14:38.
Background
Generation Scotland: Scottish Family Health Study (GS:SFHS) is a family-based biobank of 24,000 participants with rich phenotype and DNA available for genetic research. This paper describes the laboratory results from genotyping 32 single nucleotide polymorphisms (SNPs) on DNA from over 10,000 participants who attended GS:SFHS research clinics. The analysis described here was undertaken to test the quality of genetic information available to researchers. The success rate of each marker genotyped (call rate), minor allele frequency and adherence to Mendelian inheritance are presented. The few deviations in marker transmission in the 925 parent-child trios analysed were assessed as to whether they were likely to be miscalled genotypes, data or sample handling errors, or pedigree inaccuracies including non-paternity.
Methods
The first 10,450 GS:SFHS clinic participants who had spirometry and smoking data available and DNA extracted were selected. 32 SNPs were assayed, chosen as part of a replication experiment from a Genome-Wide Association Study meta-analysis of lung function.
Results
In total 325,336 genotypes were returned. The overall project pass rate (32 SNPs on 10,450 samples) was 97.29%. A total of 925 parent-child trios were assessed for transmission of the SNP markers, with 16 trios indicating evidence of inconsistency in the recorded pedigrees.
Conclusions
The Generation Scotland: Scottish Family Health Study used well-validated study methods and can produce good quality genetic data, with a low error rate. The GS:SFHS DNA samples are of high quality and the family groups were recorded and processed with accuracy during collection of the cohort.
doi:10.1186/1471-2350-14-38
PMCID: PMC3614907  PMID: 23521772
Genetics; SNP Genotyping; Parent-child trios; Error rate; Non paternity; Generation Scotland; Biobank
3.  Genome-wide association and large scale follow-up identifies 16 new loci influencing lung function 
Artigas, María Soler | Loth, Daan W | Wain, Louise V | Gharib, Sina A | Obeidat, Ma’en | Tang, Wenbo | Zhai, Guangju | Zhao, Jing Hua | Smith, Albert Vernon | Huffman, Jennifer E | Albrecht, Eva | Jackson, Catherine M | Evans, David M | Cadby, Gemma | Fornage, Myriam | Manichaikul, Ani | Lopez, Lorna M | Johnson, Toby | Aldrich, Melinda C | Aspelund, Thor | Barroso, Inês | Campbell, Harry | Cassano, Patricia A | Couper, David J | Eiriksdottir, Gudny | Franceschini, Nora | Garcia, Melissa | Gieger, Christian | Gislason, Gauti Kjartan | Grkovic, Ivica | Hammond, Christopher J | Hancock, Dana B | Harris, Tamara B | Ramasamy, Adaikalavan | Heckbert, Susan R | Heliövaara, Markku | Homuth, Georg | Hysi, Pirro G | James, Alan L | Jankovic, Stipan | Joubert, Bonnie R | Karrasch, Stefan | Klopp, Norman | Koch, Beate | Kritchevsky, Stephen B | Launer, Lenore J | Liu, Yongmei | Loehr, Laura R | Lohman, Kurt | Loos, Ruth JF | Lumley, Thomas | Al Balushi, Khalid A | Ang, Wei Q | Barr, R Graham | Beilby, John | Blakey, John D | Boban, Mladen | Boraska, Vesna | Brisman, Jonas | Britton, John R | Brusselle, Guy G | Cooper, Cyrus | Curjuric, Ivan | Dahgam, Santosh | Deary, Ian J | Ebrahim, Shah | Eijgelsheim, Mark | Francks, Clyde | Gaysina, Darya | Granell, Raquel | Gu, Xiangjun | Hankinson, John L | Hardy, Rebecca | Harris, Sarah E | Henderson, John | Henry, Amanda | Hingorani, Aroon D | Hofman, Albert | Holt, Patrick G | Hui, Jennie | Hunter, Michael L | Imboden, Medea | Jameson, Karen A | Kerr, Shona M | Kolcic, Ivana | Kronenberg, Florian | Liu, Jason Z | Marchini, Jonathan | McKeever, Tricia | Morris, Andrew D | Olin, Anna-Carin | Porteous, David J | Postma, Dirkje S | Rich, Stephen S | Ring, Susan M | Rivadeneira, Fernando | Rochat, Thierry | Sayer, Avan Aihie | Sayers, Ian | Sly, Peter D | Smith, George Davey | Sood, Akshay | Starr, John M | Uitterlinden, André G | Vonk, Judith M | Wannamethee, S Goya | Whincup, Peter H | Wijmenga, Cisca | Williams, O Dale | Wong, Andrew | Mangino, Massimo | Marciante, Kristin D | McArdle, Wendy L | Meibohm, Bernd | Morrison, Alanna C | North, Kari E | Omenaas, Ernst | Palmer, Lyle J | Pietiläinen, Kirsi H | Pin, Isabelle | Polašek, Ozren | Pouta, Anneli | Psaty, Bruce M | Hartikainen, Anna-Liisa | Rantanen, Taina | Ripatti, Samuli | Rotter, Jerome I | Rudan, Igor | Rudnicka, Alicja R | Schulz, Holger | Shin, So-Youn | Spector, Tim D | Surakka, Ida | Vitart, Veronique | Völzke, Henry | Wareham, Nicholas J | Warrington, Nicole M | Wichmann, H-Erich | Wild, Sarah H | Wilk, Jemma B | Wjst, Matthias | Wright, Alan F | Zgaga, Lina | Zemunik, Tatijana | Pennell, Craig E | Nyberg, Fredrik | Kuh, Diana | Holloway, John W | Boezen, H Marike | Lawlor, Debbie A | Morris, Richard W | Probst-Hensch, Nicole | Kaprio, Jaakko | Wilson, James F | Hayward, Caroline | Kähönen, Mika | Heinrich, Joachim | Musk, Arthur W | Jarvis, Deborah L | Gläser, Sven | Järvelin, Marjo-Riitta | Stricker, Bruno H Ch | Elliott, Paul | O’Connor, George T | Strachan, David P | London, Stephanie J | Hall, Ian P | Gudnason, Vilmundur | Tobin, Martin D
Nature Genetics  2011;43(11):1082-1090.
Pulmonary function measures reflect respiratory health and predict mortality, and are used in the diagnosis of chronic obstructive pulmonary disease (COPD). We tested genome-wide association with the forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) in 48,201 individuals of European ancestry, with follow-up of top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P<5×10−8) with pulmonary function, in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1, and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.
doi:10.1038/ng.941
PMCID: PMC3267376  PMID: 21946350
4.  Generation Scotland: Donor DNA Databank; A control DNA resource 
BMC Medical Genetics  2010;11:166.
Background
Many medical disorders of public health importance are complex diseases caused by multiple genetic, environmental and lifestyle factors. Recent technological advances have made it possible to analyse the genetic variants that predispose to complex diseases. Reliable detection of these variants requires genome-wide association studies in sufficiently large numbers of cases and controls. This approach is often hampered by difficulties in collecting appropriate control samples. The Generation Scotland: Donor DNA Databank (GS:3D) aims to help solve this problem by providing a resource of control DNA and plasma samples accessible for research.
Methods
GS:3D participants were recruited from volunteer blood donors attending Scottish National Blood Transfusion Service (SNBTS) clinics across Scotland. All participants gave full written consent for GS:3D to take spare blood from their normal donation. Participants also supplied demographic data by completing a short questionnaire.
Results
Over five thousand complete sets of samples, data and consent forms were collected. DNA and plasma were extracted and stored. The data and samples were unlinked from their original SNBTS identifier number. The plasma, DNA and demographic data are available for research. New data obtained from analysis of the resource will be fed back to GS:3D and will be made available to other researchers as appropriate.
Conclusions
Recruitment of blood donors is an efficient and cost-effective way of collecting thousands of control samples. Because the collection is large, subsets of controls can be selected, based on age range, gender, and ethnic or geographic origin. The GS:3D resource should reduce time and expense for investigators who would otherwise have had to recruit their own controls.
doi:10.1186/1471-2350-11-166
PMCID: PMC3002899  PMID: 21092308

Results 1-4 (4)