PMID- 32823649
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20200928
IS  - 2079-7737 (Print)
IS  - 2079-7737 (Electronic)
IS  - 2079-7737 (Linking)
VI  - 9
IP  - 8
DP  - 2020 Aug 13
TI  - Artificial Neural Networks Model for Predicting Type 2 Diabetes Mellitus Based on 
      VDR Gene FokI Polymorphism, Lipid Profile and Demographic Data.
LID - 10.3390/biology9080222 [doi]
LID - 222
AB  - Type 2 diabetes mellitus (T2DM) is a multifactorial disease associated with many 
      genetic polymorphisms; among them is the FokI polymorphism in the vitamin D 
      receptor (VDR) gene. In this case-control study, samples from 82 T2DM patients 
      and 82 healthy controls were examined to investigate the association of the FokI 
      polymorphism and lipid profile with T2DM in the Jordanian population. DNA was 
      extracted from blood and genotyped for the FokI polymorphism by polymerase chain 
      reaction (PCR) and DNA sequencing. Lipid profile and fasting blood sugar were 
      also measured. There were significant differences in high-density lipoprotein 
      (HDL) cholesterol and triglyceride levels between T2DM and control samples. 
      Frequencies of the FokI polymorphism (CC, CT and TT) were determined in T2DM and 
      control samples and were not significantly different. Furthermore, there was no 
      significant association between the FokI polymorphism and T2DM or lipid profile. 
      A feed-forward neural network (FNN) was used as a computational platform to 
      predict the persons with diabetes based on the FokI polymorphism, lipid profile, 
      gender and age. The accuracy of prediction reached 88% when all parameters were 
      included, 81% when the FokI polymorphism was excluded, and 72% when lipids were 
      only included. This is the first study investigating the association of the VDR 
      gene FokI polymorphism with T2DM in the Jordanian population, and it showed 
      negative association. Diabetes was predicted with high accuracy based on medical 
      data using an FNN. This highlights the great value of incorporating neural 
      network tools into large medical databases and the ability to predict patient 
      susceptibility to diabetes.
FAU - Hatmal, Ma'mon M
AU  - Hatmal MM
AUID- ORCID: 0000-0003-1745-8985
AD  - Department of Medical Laboratory Sciences, Faculty of Applied Health Sciences, 
      The Hashemite University, Zarqa 13133, Jordan.
FAU - Abderrahman, Salim M
AU  - Abderrahman SM
AD  - Department of Biology, Faculty of Science, The Hashemite University, Zarqa 13133, 
      Jordan.
FAU - Nimer, Wajeha
AU  - Nimer W
AD  - Department of Biology, Faculty of Science, The Hashemite University, Zarqa 13133, 
      Jordan.
FAU - Al-Eisawi, Zaynab
AU  - Al-Eisawi Z
AD  - Department of Medical Laboratory Sciences, Faculty of Applied Health Sciences, 
      The Hashemite University, Zarqa 13133, Jordan.
FAU - Al-Ameer, Hamzeh J
AU  - Al-Ameer HJ
AD  - Department of Biology and Biotechnology, American University of Madaba, Madaba 
      11821, Jordan.
FAU - Al-Hatamleh, Mohammad A I
AU  - Al-Hatamleh MAI
AUID- ORCID: 0000-0001-8249-9519
AD  - Department of Immunology, School of Medical Sciences, Universiti Sains Malaysia, 
      Kubang Kerian, Kelantan 16150, Malaysia.
FAU - Mohamud, Rohimah
AU  - Mohamud R
AUID- ORCID: 0000-0002-2465-6421
AD  - Department of Immunology, School of Medical Sciences, Universiti Sains Malaysia, 
      Kubang Kerian, Kelantan 16150, Malaysia.
AD  - Hospital Universiti Sains Malaysia, Kubang Kerian, Kelantan 16150, Malaysia.
FAU - Alshaer, Walhan
AU  - Alshaer W
AUID- ORCID: 0000-0003-2946-7328
AD  - Cell Therapy Center (CTC), The University of Jordan, Amman 11942, Jordan.
LA  - eng
GR  - 9/1/2017/2018/The Hashemite University/
PT  - Journal Article
DEP - 20200813
PL  - Switzerland
TA  - Biology (Basel)
JT  - Biology
JID - 101587988
PMC - PMC7465516
OTO - NOTNLM
OT  - FNN
OT  - FokI polymorphism
OT  - T2DM
OT  - VDR gene
OT  - diabetes
OT  - diabetic Jordanians
OT  - lipids
OT  - medical databases
OT  - neural network
COIS- The authors declare no conflict of interest. The funders had no role in the 
      design of the study; in the collection, analyses, or interpretation of data; in 
      the writing of the manuscript, or in the decision to publish the results.
EDAT- 2020/08/23 06:00
MHDA- 2020/08/23 06:01
PMCR- 2020/08/01
CRDT- 2020/08/23 06:00
PHST- 2020/07/12 00:00 [received]
PHST- 2020/08/04 00:00 [revised]
PHST- 2020/08/10 00:00 [accepted]
PHST- 2020/08/23 06:00 [entrez]
PHST- 2020/08/23 06:00 [pubmed]
PHST- 2020/08/23 06:01 [medline]
PHST- 2020/08/01 00:00 [pmc-release]
AID - biology9080222 [pii]
AID - biology-09-00222 [pii]
AID - 10.3390/biology9080222 [doi]
PST - epublish
SO  - Biology (Basel). 2020 Aug 13;9(8):222. doi: 10.3390/biology9080222.