Molly R Morris1, Bjoern Ch Ludwar2, Evan Swingle3, Mahelet N Mamo2, Jay H Shubrook4. 1. Department of Biological Sciences, Ohio University, Athens, OH, USA morrism@ohio.edu. 2. Longwood University, Farmville, VA, USA. 3. Department of Biological Sciences, Ohio University, Athens, OH, USA. 4. College of Osteopathic Medicine, Touro University California, Vallejo, CA, USA.
Abstract
BACKGROUND: Inexpensive screening tools are needed to identify individuals predisposed to developing diabetes mellitus (DM). Such early identification coupled with an effective intervention could help many people avoid the substantial health costs of this disease. We investigated the hypothesis that fluctuating asymmetry (FA) in fingerprints is an indicator of type 2 diabetes mellitus (T2DM). METHODS: Participants with T2DM, with T1DM, and without any indication or known family history of diabetes were fingerprinted with a Crossmatch Verifier 320 LC scanner. Asymmetry scores for each finger pair were assessed using both pattern analysis (ridge counts), and a wavelet-based analysis. RESULTS: Both methods for scoring asymmetry predicted risk of T2DM for finger pair IV, controlling for gender and age. AUC scores were significantly greater than the null for pattern asymmetry scores (finger IV AUC = 0.74), and wavelet asymmetry scores for finger pair IV (AUC = 0.73) and finger pair V (AUC = 0.73), for predicting T2DM. In addition, wavelet asymmetry scores for finger pair IV (AUC = 0.80) and finger pair V (AUC = 0.85) significantly predicted risk of T1DM. CONCLUSIONS: A diagnostic tool based on FA in the fingerprints of finger pair IV, measured using a wavelet analysis could be developed for predicting risk prior to associated health problems for both T2DM and T1DM. In addition, given that that the prints for fingers IV and V develop during the 14-17 weeks of gestation, we predict that interventions during this time period of pregnancy will be most successful.
BACKGROUND: Inexpensive screening tools are needed to identify individuals predisposed to developing diabetes mellitus (DM). Such early identification coupled with an effective intervention could help many people avoid the substantial health costs of this disease. We investigated the hypothesis that fluctuating asymmetry (FA) in fingerprints is an indicator of type 2 diabetes mellitus (T2DM). METHODS:Participants with T2DM, with T1DM, and without any indication or known family history of diabetes were fingerprinted with a Crossmatch Verifier 320 LC scanner. Asymmetry scores for each finger pair were assessed using both pattern analysis (ridge counts), and a wavelet-based analysis. RESULTS: Both methods for scoring asymmetry predicted risk of T2DM for finger pair IV, controlling for gender and age. AUC scores were significantly greater than the null for pattern asymmetry scores (finger IV AUC = 0.74), and wavelet asymmetry scores for finger pair IV (AUC = 0.73) and finger pair V (AUC = 0.73), for predicting T2DM. In addition, wavelet asymmetry scores for finger pair IV (AUC = 0.80) and finger pair V (AUC = 0.85) significantly predicted risk of T1DM. CONCLUSIONS: A diagnostic tool based on FA in the fingerprints of finger pair IV, measured using a wavelet analysis could be developed for predicting risk prior to associated health problems for both T2DM and T1DM. In addition, given that that the prints for fingers IV and V develop during the 14-17 weeks of gestation, we predict that interventions during this time period of pregnancy will be most successful.
Authors: David E Laaksonen; Jaana Lindström; Timo A Lakka; Johan G Eriksson; Leo Niskanen; Katja Wikström; Sirkka Aunola; Sirkka Keinänen-Kiukaanniemi; Mauri Laakso; Timo T Valle; Pirjo Ilanne-Parikka; Anne Louheranta; Helena Hämäläinen; Merja Rastas; Virpi Salminen; Zygimantas Cepaitis; Martti Hakumäki; Hannu Kaikkonen; Pirjo Härkönen; Jouko Sundvall; Jaakko Tuomilehto; Matti Uusitupa Journal: Diabetes Date: 2005-01 Impact factor: 9.461