Andrew Hattersley - Selected Publications#

Taken from >650 peer reviewed publications, From Google Scholar 123,000 citations, H index 160

1. Hattersley AT, Beards F, Ballantyne E, Appleton M, Harvey R, Ellard S.
Mutations in the glucokinase gene of the fetus result in reduced birth weight.
Nature Genetics, 1998 19:268-70. PMID: 9662401
659 Citations

This landmark paper studied offspring of GCK-MODY patients and demonstrated fetal genotype markedly affected birth weight by altering insulin secretion in-utero. We hypothesised that reduced fetal growth could result from a fetal genetic predisposition to T2D (the fetal insulin hypothesis) as subsequently confirmed by polygenic studies.

2. Pearson ER, Starkey BJ, Powell RJ, Gribble FM, Clark PM, Hattersley AT.
Genetic cause of hyperglycaemia and response to treatment in diabetes.
Lancet. 2003 362:1275-81 PMID: 14575972
630 citations

This double blind cross over study established that patients with the commonest form of familial monogenic diabetes due to HNF1A mutations were acutely sensitive to glucose lowering with sulfonylurea medication. This pharmacogentic response resulted in patients being able to discontinue insulin and achieve excellent control on tablets which lead to genetic testing for familial monogenic diabetes being adopted throughout the world.

3. Gloyn AL, Pearson ER, et al, Ellard S, Njolstad PR, Ashcroft FM, Hattersley AT.
Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes.
N Engl J Med 2004;350: 1838-49 PMID: 15115830
1,302 citations

This study showed that the commonest cause of monogenic diabetes were activating mutations in the KCNJ11 gene that encoded Kir6.2 subunit of the beta-cell potassium channel and showed the mechanism was by preventing the beta-cell closing in the presence of ATP.

4. Pearson ER, Flechtner I, Njolstad PR, et al Sovik O, Polak M, Hattersley AT.
Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations.
N Engl J Med 2006;3:467-77 PMID: 16885550
1025 citations

This study dramatically changed patient care as 90% of insulin-dependent patients with Kir6.2 mutations could transfer from insulin injections to sulphonylurea tablets and improve their glycaemic control. Physiological studies established the key role of non-KATP pathways.

5. Frayling TM, Timpson NJ, Weedon MN et al Smith GD, Hattersley AT*, McCarthy MI* (*Joint)
A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity.
Science. 2007;316(5826):889-94 PMID: 17434869
4911 citations

This landmark study describes the first common gene variant that altered BMI. This collaborative study of 39,000 subjects by 42 scientists was jointly led by Exeter and Oxford

6. Weedon MN, Cebola I, Patch AM, Flanagan SE, De Franco E, et al Ellard S*, Ferrer J*, Hattersley AT* (joint).
Recessive mutations in a distal PTF1A enhancer cause isolated pancreatic agenesis.
Nature Genetics 2014 Jan;46(1):61-4 PMID: 24212882
255 citations

This is the first study to identify novel disease-causing non-coding variants by combining genome sequencing with epigenomic annotation in hESC-derived pancreatic progenitors. We showed mutations which disrupt a regulatory enhancer of PTF1A cause isolated pancreatic agenesis.

7. Flanagan SE, Haapaniemi E, Russell MA, et al Morgan NG, Ellard S, Hattersley AT.
Activating germline mutations in STAT3 cause early-onset multi-organ autoimmune disease.
Nature Genetics.2014 46:812-814. PMID: 25038750
409 citations

This was amongst the first studies to use next-generation sequencing to find a novel monogenic diabetes gene. The results highlighted a role for STAT3 in beta cell autoimmunity.

8. De Franco E, Flanagan SE, Houghton JA, et al, Temple IK, Ellard S, Hattersley AT
The effect of early, comprehensive genomic testing on clinical care in neonatal diabetes: an international cohort study.
Lancet. 2015 5; 386957-63. PMID: 26231457
251 citations

A comprehensive analysis of the largest neonatal-diabetes cohort showed that genetics predicts the best diabetes treatment and development of related features. This model represents a new framework where genetic testing defines likely clinical outcome rather than confirming the clinical diagnosis.

9. Thomas NJ, Jones SE, Weedon MN, Shields BM, Oram RA, Hattersley AT.
Frequency and phenotype of type 1 diabetes in the first six decades of life: across-sectional, genetically stratified survival analysis from UK Biobank.
Lancet Diabetes Endocrinol. 2017 (Dec) S2213-8587 30362-5. PMID: 29199115
268 citations

This study used a novel genetic methodology to define the prevalence and characteristics of Type 1 diabetes. The findings were striking there was nearly as much Type 1 diabetes diagnosed after 30 yrs as before and the severity was similar.

10. Dennis JM, Shields BM, Henley WE, Jones AG, Hattersley AT.
Disease progression and treatment response in data-driven subgroups of type 2 diabetes compared with models based on simple clinical features: an analysis using clinical trial data.
Lancet Diabetes Endocrinol. 2019 Jun;7(6):442-451. PMID: 31047901
152 citations

This highly cited study showed that the prediction of disease progression and treatment response in Type 2 diabetes was best done by modeling the simple quantitative clinical variables rather than putting patients in the highly publicised data driven subgroups.