to_sql method turns datetime64 index to time zone aware in postgres
I have a `pandas` `Dataframe` with an index which is of type `datetime64[ns]`.
when I use the `to_sql` method i expect the index to be created as a `timestamp` postgres column, however it is creates a `timestamptz` column.

Note that when the `datetime64[ns]` column is not an index but rather a normal column, this doesn't happen.

pandas 0.23.4, psycopg2 2.7.4, sqlalchemy 1.2.7, PostgreSQL 9.6.6

---
*example*

```python
dates = pd.date_range('2018-01-01', periods=5, freq='6h')
df_test = pd.DataFrame({'nums': range(5)}, index=dates)
```
<details>

|                     | nums |
|---------------------|------|
| 2018-01-01 00:00:00 | 0    |
| 2018-01-01 06:00:00 | 1    |
| 2018-01-01 12:00:00 | 2    |

</details>

inserting to postgres
```python
df_test.to_sql('foo_table',postgres_uri,schema='data_test',index_label='info_date')
```
when reading from the database I get the index with different type
```python
df_db = pd.read_sql_table('foo_table',postgres_uri,schema='data_test',index_col='info_date')
```
<details>

|                           | nums |
|---------------------------|------|
| info_date                 |      |
| 2018-01-01 00:00:00+00:00 | 0    |
| 2018-01-01 06:00:00+00:00 | 1    |
| 2018-01-01 12:00:00+00:00 | 2    |

</details>
As you can see `info_date` is of type `datetime64[ns, UTC]`

not sure if it's a sqlalchemy or pandas question.
reported because of my [question](https://stackoverflow.com/questions/52986158/pandas-to-sql-turns-datetime64-index-to-time-zone-aware) on SO